{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "import warnings\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "import seaborn as sns\n",
    "import warnings\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.tree import ExtraTreeRegressor\n",
    "from xgboost import XGBRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.ensemble import AdaBoostRegressor\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.ensemble import BaggingRegressor\n",
    "\n",
    "from sklearn.metrics import mean_squared_error as MSE\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import mean_absolute_error #平方绝对误差\n",
    "from sklearn.metrics import r2_score#R square\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号\n",
    "#显示所有列\n",
    "pd.set_option('display.max_columns', None)\n",
    "#显示所有行\n",
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_325 = pd.read_excel(\"3-数据清洗后325样本数据.xlsx\", na_values=np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(268, 203)"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_325.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>样本编号</th>\n",
       "      <th>时间</th>\n",
       "      <th>RON损失</th>\n",
       "      <th>原料性质：硫含量</th>\n",
       "      <th>原料性质：辛烷值</th>\n",
       "      <th>原料性质：饱和烃</th>\n",
       "      <th>原料性质：烯烃</th>\n",
       "      <th>原料性质：芳烃</th>\n",
       "      <th>原料性质：溴值</th>\n",
       "      <th>原料性质：密度</th>\n",
       "      <th>...</th>\n",
       "      <th>S-ZORB.AT-0011.DACA.PV</th>\n",
       "      <th>S-ZORB.FT_1204.DACA.PV</th>\n",
       "      <th>S-ZORB.LC_5102.PIDA.PV</th>\n",
       "      <th>S-ZORB.TE_1102.DACA.PV</th>\n",
       "      <th>S-ZORB.CAL.LINE.PV</th>\n",
       "      <th>S-ZORB.CAL.CANGLIANG.PV</th>\n",
       "      <th>S-ZORB.CAL.SPEED.PV</th>\n",
       "      <th>S-ZORB.FT_1503.TOTALIZERA.PV</th>\n",
       "      <th>S-ZORB.FT_1504.TOTALIZERA.PV</th>\n",
       "      <th>S-ZORB.PC_1001A.PV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2020/5/26 8:00:00</td>\n",
       "      <td>1.38</td>\n",
       "      <td>188.000000</td>\n",
       "      <td>90.6</td>\n",
       "      <td>53.230000</td>\n",
       "      <td>24.400000</td>\n",
       "      <td>22.370000</td>\n",
       "      <td>61.487143</td>\n",
       "      <td>726.085714</td>\n",
       "      <td>...</td>\n",
       "      <td>0.496243</td>\n",
       "      <td>18.292067</td>\n",
       "      <td>42.015425</td>\n",
       "      <td>425.929515</td>\n",
       "      <td>0.282564</td>\n",
       "      <td>37.804650</td>\n",
       "      <td>3.324945</td>\n",
       "      <td>3.906312e+07</td>\n",
       "      <td>3.960876e+07</td>\n",
       "      <td>0.353271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2020/5/21 8:00:00</td>\n",
       "      <td>1.18</td>\n",
       "      <td>169.000000</td>\n",
       "      <td>90.5</td>\n",
       "      <td>52.300000</td>\n",
       "      <td>26.400000</td>\n",
       "      <td>21.300000</td>\n",
       "      <td>61.880000</td>\n",
       "      <td>731.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.491385</td>\n",
       "      <td>19.842605</td>\n",
       "      <td>40.903878</td>\n",
       "      <td>421.534365</td>\n",
       "      <td>0.281381</td>\n",
       "      <td>37.876006</td>\n",
       "      <td>3.321169</td>\n",
       "      <td>3.881058e+07</td>\n",
       "      <td>3.938930e+07</td>\n",
       "      <td>0.354504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2020/5/19 8:00:00</td>\n",
       "      <td>1.38</td>\n",
       "      <td>177.000000</td>\n",
       "      <td>90.7</td>\n",
       "      <td>52.300000</td>\n",
       "      <td>26.314286</td>\n",
       "      <td>21.385714</td>\n",
       "      <td>61.722857</td>\n",
       "      <td>729.614286</td>\n",
       "      <td>...</td>\n",
       "      <td>0.495483</td>\n",
       "      <td>26.994896</td>\n",
       "      <td>42.103142</td>\n",
       "      <td>425.258420</td>\n",
       "      <td>0.282277</td>\n",
       "      <td>37.907927</td>\n",
       "      <td>3.319569</td>\n",
       "      <td>3.869381e+07</td>\n",
       "      <td>3.931262e+07</td>\n",
       "      <td>0.350181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2020/5/14 8:00:00</td>\n",
       "      <td>1.38</td>\n",
       "      <td>159.000000</td>\n",
       "      <td>90.4</td>\n",
       "      <td>52.300000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>21.600000</td>\n",
       "      <td>61.330000</td>\n",
       "      <td>725.400000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.490180</td>\n",
       "      <td>26.324458</td>\n",
       "      <td>41.970416</td>\n",
       "      <td>424.406195</td>\n",
       "      <td>0.282275</td>\n",
       "      <td>39.177396</td>\n",
       "      <td>3.210211</td>\n",
       "      <td>3.841086e+07</td>\n",
       "      <td>3.912020e+07</td>\n",
       "      <td>0.353930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2020/5/12 8:00:00</td>\n",
       "      <td>1.28</td>\n",
       "      <td>173.000000</td>\n",
       "      <td>89.6</td>\n",
       "      <td>52.242857</td>\n",
       "      <td>26.671429</td>\n",
       "      <td>21.085714</td>\n",
       "      <td>61.332857</td>\n",
       "      <td>725.428571</td>\n",
       "      <td>...</td>\n",
       "      <td>0.501194</td>\n",
       "      <td>30.224367</td>\n",
       "      <td>42.900094</td>\n",
       "      <td>428.514740</td>\n",
       "      <td>0.282963</td>\n",
       "      <td>39.508370</td>\n",
       "      <td>3.178832</td>\n",
       "      <td>3.828300e+07</td>\n",
       "      <td>3.904595e+07</td>\n",
       "      <td>0.358053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>2020/5/7 8:00:00</td>\n",
       "      <td>1.41</td>\n",
       "      <td>163.000000</td>\n",
       "      <td>91.0</td>\n",
       "      <td>52.100000</td>\n",
       "      <td>28.100000</td>\n",
       "      <td>19.800000</td>\n",
       "      <td>61.340000</td>\n",
       "      <td>725.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.491737</td>\n",
       "      <td>27.873024</td>\n",
       "      <td>42.006524</td>\n",
       "      <td>427.458155</td>\n",
       "      <td>0.285585</td>\n",
       "      <td>39.458643</td>\n",
       "      <td>3.190527</td>\n",
       "      <td>3.794810e+07</td>\n",
       "      <td>3.887028e+07</td>\n",
       "      <td>0.350235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9</td>\n",
       "      <td>2020/4/29 8:00:00</td>\n",
       "      <td>1.10</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>90.4</td>\n",
       "      <td>49.857143</td>\n",
       "      <td>29.071429</td>\n",
       "      <td>21.071429</td>\n",
       "      <td>61.337143</td>\n",
       "      <td>725.442857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.494778</td>\n",
       "      <td>28.024165</td>\n",
       "      <td>42.003779</td>\n",
       "      <td>424.310965</td>\n",
       "      <td>0.284122</td>\n",
       "      <td>39.889699</td>\n",
       "      <td>3.147285</td>\n",
       "      <td>3.743862e+07</td>\n",
       "      <td>3.859890e+07</td>\n",
       "      <td>0.350821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>2020/4/28 8:00:00</td>\n",
       "      <td>1.40</td>\n",
       "      <td>159.000000</td>\n",
       "      <td>90.2</td>\n",
       "      <td>50.214286</td>\n",
       "      <td>28.942857</td>\n",
       "      <td>20.842857</td>\n",
       "      <td>61.334286</td>\n",
       "      <td>725.385714</td>\n",
       "      <td>...</td>\n",
       "      <td>0.501083</td>\n",
       "      <td>27.558598</td>\n",
       "      <td>42.011845</td>\n",
       "      <td>424.629485</td>\n",
       "      <td>0.284169</td>\n",
       "      <td>39.948040</td>\n",
       "      <td>3.143236</td>\n",
       "      <td>3.737556e+07</td>\n",
       "      <td>3.856812e+07</td>\n",
       "      <td>0.340288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11</td>\n",
       "      <td>2020/4/23 8:00:00</td>\n",
       "      <td>1.30</td>\n",
       "      <td>85.000000</td>\n",
       "      <td>90.2</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>28.300000</td>\n",
       "      <td>19.700000</td>\n",
       "      <td>61.320000</td>\n",
       "      <td>725.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.497077</td>\n",
       "      <td>15.975918</td>\n",
       "      <td>41.852655</td>\n",
       "      <td>421.826745</td>\n",
       "      <td>0.277151</td>\n",
       "      <td>40.562405</td>\n",
       "      <td>2.977696</td>\n",
       "      <td>3.704518e+07</td>\n",
       "      <td>3.843288e+07</td>\n",
       "      <td>0.349968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12</td>\n",
       "      <td>2020/4/21 8:00:00</td>\n",
       "      <td>1.30</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>90.2</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>28.122222</td>\n",
       "      <td>18.877778</td>\n",
       "      <td>61.255556</td>\n",
       "      <td>723.522222</td>\n",
       "      <td>...</td>\n",
       "      <td>0.491552</td>\n",
       "      <td>16.292095</td>\n",
       "      <td>41.990558</td>\n",
       "      <td>421.586110</td>\n",
       "      <td>0.276983</td>\n",
       "      <td>40.618898</td>\n",
       "      <td>2.971716</td>\n",
       "      <td>3.691542e+07</td>\n",
       "      <td>3.837698e+07</td>\n",
       "      <td>0.350342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14</td>\n",
       "      <td>2020/4/14 8:00:00</td>\n",
       "      <td>1.40</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>86.8</td>\n",
       "      <td>56.500000</td>\n",
       "      <td>27.500000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>61.030000</td>\n",
       "      <td>718.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.491274</td>\n",
       "      <td>24.858577</td>\n",
       "      <td>41.986386</td>\n",
       "      <td>423.489335</td>\n",
       "      <td>0.277613</td>\n",
       "      <td>39.385355</td>\n",
       "      <td>3.064397</td>\n",
       "      <td>3.647651e+07</td>\n",
       "      <td>3.815302e+07</td>\n",
       "      <td>0.352959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>15</td>\n",
       "      <td>2020/4/7 8:00:00</td>\n",
       "      <td>1.70</td>\n",
       "      <td>121.000000</td>\n",
       "      <td>87.8</td>\n",
       "      <td>55.700000</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>17.100000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>715.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493202</td>\n",
       "      <td>27.990915</td>\n",
       "      <td>42.023992</td>\n",
       "      <td>422.610860</td>\n",
       "      <td>0.276967</td>\n",
       "      <td>37.064555</td>\n",
       "      <td>3.257477</td>\n",
       "      <td>3.606804e+07</td>\n",
       "      <td>3.791104e+07</td>\n",
       "      <td>0.347922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>16</td>\n",
       "      <td>2020/4/3 8:00:00</td>\n",
       "      <td>1.70</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>88.4</td>\n",
       "      <td>56.557143</td>\n",
       "      <td>26.285714</td>\n",
       "      <td>17.157143</td>\n",
       "      <td>61.011429</td>\n",
       "      <td>716.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.497189</td>\n",
       "      <td>20.698849</td>\n",
       "      <td>41.996880</td>\n",
       "      <td>426.063900</td>\n",
       "      <td>0.277969</td>\n",
       "      <td>37.817228</td>\n",
       "      <td>3.195393</td>\n",
       "      <td>3.581613e+07</td>\n",
       "      <td>3.777479e+07</td>\n",
       "      <td>0.350079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>18</td>\n",
       "      <td>2020/3/27 8:00:00</td>\n",
       "      <td>1.51</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>88.0</td>\n",
       "      <td>56.342857</td>\n",
       "      <td>23.828571</td>\n",
       "      <td>19.828571</td>\n",
       "      <td>61.191429</td>\n",
       "      <td>719.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.497448</td>\n",
       "      <td>23.081207</td>\n",
       "      <td>42.007099</td>\n",
       "      <td>424.965160</td>\n",
       "      <td>0.275221</td>\n",
       "      <td>36.948349</td>\n",
       "      <td>3.262378</td>\n",
       "      <td>3.534354e+07</td>\n",
       "      <td>3.753607e+07</td>\n",
       "      <td>0.350130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>19</td>\n",
       "      <td>2020/3/25 8:24:26</td>\n",
       "      <td>1.11</td>\n",
       "      <td>98.170000</td>\n",
       "      <td>88.2</td>\n",
       "      <td>55.914286</td>\n",
       "      <td>22.942857</td>\n",
       "      <td>21.142857</td>\n",
       "      <td>61.277143</td>\n",
       "      <td>720.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.672585</td>\n",
       "      <td>25.365019</td>\n",
       "      <td>42.445853</td>\n",
       "      <td>423.928465</td>\n",
       "      <td>0.281234</td>\n",
       "      <td>36.803149</td>\n",
       "      <td>3.414192</td>\n",
       "      <td>3.522192e+07</td>\n",
       "      <td>3.746738e+07</td>\n",
       "      <td>0.349789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20</td>\n",
       "      <td>2020/3/24 8:00:00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>88.8</td>\n",
       "      <td>55.700000</td>\n",
       "      <td>22.500000</td>\n",
       "      <td>21.800000</td>\n",
       "      <td>61.320000</td>\n",
       "      <td>721.400000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.498617</td>\n",
       "      <td>31.646892</td>\n",
       "      <td>42.005725</td>\n",
       "      <td>424.685800</td>\n",
       "      <td>0.285215</td>\n",
       "      <td>36.573184</td>\n",
       "      <td>3.575398</td>\n",
       "      <td>3.515411e+07</td>\n",
       "      <td>3.743258e+07</td>\n",
       "      <td>0.349630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>21</td>\n",
       "      <td>2020/3/19 8:19:04</td>\n",
       "      <td>1.51</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>88.1</td>\n",
       "      <td>56.414286</td>\n",
       "      <td>23.142857</td>\n",
       "      <td>20.442857</td>\n",
       "      <td>62.098571</td>\n",
       "      <td>722.257143</td>\n",
       "      <td>...</td>\n",
       "      <td>0.503623</td>\n",
       "      <td>54.421927</td>\n",
       "      <td>41.986496</td>\n",
       "      <td>424.651615</td>\n",
       "      <td>0.285987</td>\n",
       "      <td>36.605458</td>\n",
       "      <td>3.568681</td>\n",
       "      <td>3.480798e+07</td>\n",
       "      <td>3.726364e+07</td>\n",
       "      <td>0.350443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>22</td>\n",
       "      <td>2020/3/17 8:00:00</td>\n",
       "      <td>1.01</td>\n",
       "      <td>57.000000</td>\n",
       "      <td>88.2</td>\n",
       "      <td>56.700000</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>19.900000</td>\n",
       "      <td>62.410000</td>\n",
       "      <td>722.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.499469</td>\n",
       "      <td>50.719780</td>\n",
       "      <td>41.961311</td>\n",
       "      <td>421.649090</td>\n",
       "      <td>0.292024</td>\n",
       "      <td>35.751794</td>\n",
       "      <td>3.742808</td>\n",
       "      <td>3.467803e+07</td>\n",
       "      <td>3.719708e+07</td>\n",
       "      <td>0.349825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>23</td>\n",
       "      <td>2020/3/13 8:00:00</td>\n",
       "      <td>1.61</td>\n",
       "      <td>148.000000</td>\n",
       "      <td>89.6</td>\n",
       "      <td>56.585714</td>\n",
       "      <td>21.514286</td>\n",
       "      <td>21.900000</td>\n",
       "      <td>62.410000</td>\n",
       "      <td>722.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.491960</td>\n",
       "      <td>77.720622</td>\n",
       "      <td>41.521537</td>\n",
       "      <td>426.130985</td>\n",
       "      <td>0.292224</td>\n",
       "      <td>35.621330</td>\n",
       "      <td>3.749605</td>\n",
       "      <td>3.440717e+07</td>\n",
       "      <td>3.706533e+07</td>\n",
       "      <td>0.350634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>24</td>\n",
       "      <td>2020/3/10 8:00:00</td>\n",
       "      <td>1.41</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>89.0</td>\n",
       "      <td>56.500000</td>\n",
       "      <td>20.100000</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>62.410000</td>\n",
       "      <td>722.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.488307</td>\n",
       "      <td>80.912347</td>\n",
       "      <td>41.977798</td>\n",
       "      <td>427.419780</td>\n",
       "      <td>0.292619</td>\n",
       "      <td>35.711137</td>\n",
       "      <td>3.742039</td>\n",
       "      <td>3.419926e+07</td>\n",
       "      <td>3.696766e+07</td>\n",
       "      <td>0.350879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>25</td>\n",
       "      <td>2020/3/6 8:00:00</td>\n",
       "      <td>1.41</td>\n",
       "      <td>222.000000</td>\n",
       "      <td>89.3</td>\n",
       "      <td>55.128571</td>\n",
       "      <td>22.557143</td>\n",
       "      <td>22.314286</td>\n",
       "      <td>63.655714</td>\n",
       "      <td>723.742857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.487806</td>\n",
       "      <td>92.197036</td>\n",
       "      <td>41.221145</td>\n",
       "      <td>427.982850</td>\n",
       "      <td>0.293469</td>\n",
       "      <td>35.939728</td>\n",
       "      <td>3.720288</td>\n",
       "      <td>3.391231e+07</td>\n",
       "      <td>3.684692e+07</td>\n",
       "      <td>0.352470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>26</td>\n",
       "      <td>2020/3/3 8:00:00</td>\n",
       "      <td>1.51</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>89.2</td>\n",
       "      <td>54.100000</td>\n",
       "      <td>24.400000</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>64.590000</td>\n",
       "      <td>724.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493796</td>\n",
       "      <td>78.434768</td>\n",
       "      <td>42.694986</td>\n",
       "      <td>427.484970</td>\n",
       "      <td>0.294629</td>\n",
       "      <td>35.545138</td>\n",
       "      <td>3.792150</td>\n",
       "      <td>3.369577e+07</td>\n",
       "      <td>3.675443e+07</td>\n",
       "      <td>0.349980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>27</td>\n",
       "      <td>2020/2/28 8:00:00</td>\n",
       "      <td>1.41</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>88.7</td>\n",
       "      <td>55.185714</td>\n",
       "      <td>21.085714</td>\n",
       "      <td>23.728571</td>\n",
       "      <td>64.590000</td>\n",
       "      <td>724.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493555</td>\n",
       "      <td>79.476468</td>\n",
       "      <td>43.107891</td>\n",
       "      <td>425.670745</td>\n",
       "      <td>0.294139</td>\n",
       "      <td>35.705946</td>\n",
       "      <td>3.772647</td>\n",
       "      <td>3.341145e+07</td>\n",
       "      <td>3.662938e+07</td>\n",
       "      <td>0.347576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>28</td>\n",
       "      <td>2020/2/25 8:00:00</td>\n",
       "      <td>1.11</td>\n",
       "      <td>170.000000</td>\n",
       "      <td>89.0</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>18.600000</td>\n",
       "      <td>25.400000</td>\n",
       "      <td>64.590000</td>\n",
       "      <td>724.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493944</td>\n",
       "      <td>91.297853</td>\n",
       "      <td>39.701848</td>\n",
       "      <td>426.303780</td>\n",
       "      <td>0.294642</td>\n",
       "      <td>35.860610</td>\n",
       "      <td>3.760765</td>\n",
       "      <td>3.319383e+07</td>\n",
       "      <td>3.653298e+07</td>\n",
       "      <td>0.350274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>29</td>\n",
       "      <td>2020/2/21 8:00:00</td>\n",
       "      <td>1.41</td>\n",
       "      <td>206.000000</td>\n",
       "      <td>89.7</td>\n",
       "      <td>55.809524</td>\n",
       "      <td>19.514286</td>\n",
       "      <td>24.676190</td>\n",
       "      <td>65.214762</td>\n",
       "      <td>724.676190</td>\n",
       "      <td>...</td>\n",
       "      <td>0.491904</td>\n",
       "      <td>82.058983</td>\n",
       "      <td>41.833351</td>\n",
       "      <td>426.015940</td>\n",
       "      <td>0.294578</td>\n",
       "      <td>36.463434</td>\n",
       "      <td>3.695138</td>\n",
       "      <td>3.291243e+07</td>\n",
       "      <td>3.640393e+07</td>\n",
       "      <td>0.350299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>30</td>\n",
       "      <td>2020/2/18 8:00:00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>185.000000</td>\n",
       "      <td>89.2</td>\n",
       "      <td>55.666667</td>\n",
       "      <td>20.200000</td>\n",
       "      <td>24.133333</td>\n",
       "      <td>65.683333</td>\n",
       "      <td>724.733333</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493851</td>\n",
       "      <td>76.510345</td>\n",
       "      <td>39.432224</td>\n",
       "      <td>426.399895</td>\n",
       "      <td>0.295632</td>\n",
       "      <td>35.716512</td>\n",
       "      <td>3.800442</td>\n",
       "      <td>3.270305e+07</td>\n",
       "      <td>3.630571e+07</td>\n",
       "      <td>0.350219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>31</td>\n",
       "      <td>2020/2/14 8:00:00</td>\n",
       "      <td>1.71</td>\n",
       "      <td>172.000000</td>\n",
       "      <td>89.1</td>\n",
       "      <td>55.476190</td>\n",
       "      <td>21.114286</td>\n",
       "      <td>23.409524</td>\n",
       "      <td>66.308095</td>\n",
       "      <td>724.809524</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493944</td>\n",
       "      <td>76.105945</td>\n",
       "      <td>40.115808</td>\n",
       "      <td>424.573190</td>\n",
       "      <td>0.296132</td>\n",
       "      <td>35.948945</td>\n",
       "      <td>3.779360</td>\n",
       "      <td>3.242158e+07</td>\n",
       "      <td>3.617385e+07</td>\n",
       "      <td>0.350573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>32</td>\n",
       "      <td>2020/2/11 8:00:00</td>\n",
       "      <td>1.41</td>\n",
       "      <td>133.000000</td>\n",
       "      <td>88.5</td>\n",
       "      <td>55.333333</td>\n",
       "      <td>21.800000</td>\n",
       "      <td>22.866667</td>\n",
       "      <td>66.776667</td>\n",
       "      <td>724.866667</td>\n",
       "      <td>...</td>\n",
       "      <td>0.493610</td>\n",
       "      <td>84.654931</td>\n",
       "      <td>41.033284</td>\n",
       "      <td>426.951155</td>\n",
       "      <td>0.299715</td>\n",
       "      <td>36.842063</td>\n",
       "      <td>3.689150</td>\n",
       "      <td>3.222169e+07</td>\n",
       "      <td>3.607842e+07</td>\n",
       "      <td>0.350038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>33</td>\n",
       "      <td>2020/2/7 8:00:00</td>\n",
       "      <td>1.11</td>\n",
       "      <td>189.000000</td>\n",
       "      <td>88.4</td>\n",
       "      <td>55.142857</td>\n",
       "      <td>22.714286</td>\n",
       "      <td>22.142857</td>\n",
       "      <td>67.401429</td>\n",
       "      <td>724.942857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.487120</td>\n",
       "      <td>84.296083</td>\n",
       "      <td>38.800305</td>\n",
       "      <td>427.027945</td>\n",
       "      <td>0.298898</td>\n",
       "      <td>36.908064</td>\n",
       "      <td>3.679168</td>\n",
       "      <td>3.195289e+07</td>\n",
       "      <td>3.594744e+07</td>\n",
       "      <td>0.350214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>34</td>\n",
       "      <td>2020/2/4 8:00:00</td>\n",
       "      <td>0.91</td>\n",
       "      <td>144.000000</td>\n",
       "      <td>88.1</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>21.600000</td>\n",
       "      <td>67.870000</td>\n",
       "      <td>725.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.502993</td>\n",
       "      <td>84.364933</td>\n",
       "      <td>42.461636</td>\n",
       "      <td>426.916015</td>\n",
       "      <td>0.299187</td>\n",
       "      <td>37.099652</td>\n",
       "      <td>3.665850</td>\n",
       "      <td>3.175291e+07</td>\n",
       "      <td>3.585419e+07</td>\n",
       "      <td>0.352319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>302</td>\n",
       "      <td>2017/6/7 8:00:00</td>\n",
       "      <td>1.25</td>\n",
       "      <td>254.714286</td>\n",
       "      <td>90.4</td>\n",
       "      <td>43.240000</td>\n",
       "      <td>33.900000</td>\n",
       "      <td>22.860000</td>\n",
       "      <td>60.730000</td>\n",
       "      <td>724.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.682904</td>\n",
       "      <td>31.515007</td>\n",
       "      <td>48.510241</td>\n",
       "      <td>425.907478</td>\n",
       "      <td>0.285346</td>\n",
       "      <td>24.674995</td>\n",
       "      <td>5.204484</td>\n",
       "      <td>3.296502e+06</td>\n",
       "      <td>3.471070e+06</td>\n",
       "      <td>-107.474335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>179</td>\n",
       "      <td>2018/6/25 8:00:00</td>\n",
       "      <td>0.54</td>\n",
       "      <td>231.428571</td>\n",
       "      <td>90.1</td>\n",
       "      <td>50.400000</td>\n",
       "      <td>23.400000</td>\n",
       "      <td>26.200000</td>\n",
       "      <td>43.820000</td>\n",
       "      <td>735.150000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.492326</td>\n",
       "      <td>42.169189</td>\n",
       "      <td>38.995439</td>\n",
       "      <td>424.697885</td>\n",
       "      <td>0.289957</td>\n",
       "      <td>24.325651</td>\n",
       "      <td>5.575779</td>\n",
       "      <td>7.480456e+05</td>\n",
       "      <td>1.077253e+06</td>\n",
       "      <td>-9.200040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>227</td>\n",
       "      <td>2017/12/29 8:00:00</td>\n",
       "      <td>1.32</td>\n",
       "      <td>194.142857</td>\n",
       "      <td>90.5</td>\n",
       "      <td>55.800000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>20.200000</td>\n",
       "      <td>56.900000</td>\n",
       "      <td>729.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.689663</td>\n",
       "      <td>34.457438</td>\n",
       "      <td>44.986011</td>\n",
       "      <td>428.322047</td>\n",
       "      <td>0.278856</td>\n",
       "      <td>32.451271</td>\n",
       "      <td>3.960014</td>\n",
       "      <td>1.351063e+07</td>\n",
       "      <td>1.648705e+07</td>\n",
       "      <td>-54.873207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>280</td>\n",
       "      <td>2017/7/28 8:00:00</td>\n",
       "      <td>1.15</td>\n",
       "      <td>206.428571</td>\n",
       "      <td>89.9</td>\n",
       "      <td>45.090000</td>\n",
       "      <td>31.040000</td>\n",
       "      <td>23.870000</td>\n",
       "      <td>55.730000</td>\n",
       "      <td>728.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.663027</td>\n",
       "      <td>38.795700</td>\n",
       "      <td>44.989558</td>\n",
       "      <td>422.002772</td>\n",
       "      <td>0.285701</td>\n",
       "      <td>22.418918</td>\n",
       "      <td>6.092723</td>\n",
       "      <td>5.608772e+06</td>\n",
       "      <td>6.716107e+06</td>\n",
       "      <td>-94.388200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>320</td>\n",
       "      <td>2017/4/28 8:00:00</td>\n",
       "      <td>1.25</td>\n",
       "      <td>271.428571</td>\n",
       "      <td>89.5</td>\n",
       "      <td>47.190000</td>\n",
       "      <td>31.300000</td>\n",
       "      <td>21.510000</td>\n",
       "      <td>52.020000</td>\n",
       "      <td>725.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.686593</td>\n",
       "      <td>28.237637</td>\n",
       "      <td>41.766124</td>\n",
       "      <td>421.294620</td>\n",
       "      <td>0.292044</td>\n",
       "      <td>20.083964</td>\n",
       "      <td>6.547161</td>\n",
       "      <td>1.617744e+06</td>\n",
       "      <td>1.127116e+06</td>\n",
       "      <td>-117.737970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>17</td>\n",
       "      <td>2020/3/31 8:00:00</td>\n",
       "      <td>1.10</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>87.2</td>\n",
       "      <td>57.200000</td>\n",
       "      <td>25.600000</td>\n",
       "      <td>17.200000</td>\n",
       "      <td>61.020000</td>\n",
       "      <td>717.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.499377</td>\n",
       "      <td>26.597893</td>\n",
       "      <td>41.995972</td>\n",
       "      <td>424.525475</td>\n",
       "      <td>0.277341</td>\n",
       "      <td>37.682487</td>\n",
       "      <td>3.204449</td>\n",
       "      <td>3.561732e+07</td>\n",
       "      <td>3.767269e+07</td>\n",
       "      <td>0.350337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>278</td>\n",
       "      <td>2017/8/2 8:00:00</td>\n",
       "      <td>1.05</td>\n",
       "      <td>206.428571</td>\n",
       "      <td>89.5</td>\n",
       "      <td>45.090000</td>\n",
       "      <td>31.040000</td>\n",
       "      <td>23.870000</td>\n",
       "      <td>55.730000</td>\n",
       "      <td>728.100000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.671899</td>\n",
       "      <td>45.121040</td>\n",
       "      <td>44.995582</td>\n",
       "      <td>423.088040</td>\n",
       "      <td>0.296388</td>\n",
       "      <td>22.861628</td>\n",
       "      <td>6.241138</td>\n",
       "      <td>5.859340e+06</td>\n",
       "      <td>7.049883e+06</td>\n",
       "      <td>-93.105246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>299</td>\n",
       "      <td>2017/6/14 8:00:00</td>\n",
       "      <td>1.15</td>\n",
       "      <td>245.000000</td>\n",
       "      <td>89.8</td>\n",
       "      <td>45.690000</td>\n",
       "      <td>34.670000</td>\n",
       "      <td>19.640000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>725.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.674468</td>\n",
       "      <td>48.743563</td>\n",
       "      <td>41.764215</td>\n",
       "      <td>419.464813</td>\n",
       "      <td>0.288439</td>\n",
       "      <td>23.565331</td>\n",
       "      <td>5.714073</td>\n",
       "      <td>3.675311e+06</td>\n",
       "      <td>3.877717e+06</td>\n",
       "      <td>-105.678200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>108</td>\n",
       "      <td>2019/5/10 8:00:00</td>\n",
       "      <td>1.68</td>\n",
       "      <td>263.000000</td>\n",
       "      <td>90.6</td>\n",
       "      <td>50.400000</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>22.400000</td>\n",
       "      <td>52.282500</td>\n",
       "      <td>729.350000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.490921</td>\n",
       "      <td>70.023827</td>\n",
       "      <td>39.988794</td>\n",
       "      <td>425.348090</td>\n",
       "      <td>0.312376</td>\n",
       "      <td>33.171430</td>\n",
       "      <td>4.089284</td>\n",
       "      <td>1.757141e+07</td>\n",
       "      <td>2.094580e+07</td>\n",
       "      <td>0.350027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>268</td>\n",
       "      <td>2017/8/25 8:00:00</td>\n",
       "      <td>1.34</td>\n",
       "      <td>300.714286</td>\n",
       "      <td>89.6</td>\n",
       "      <td>46.850000</td>\n",
       "      <td>30.490000</td>\n",
       "      <td>22.660000</td>\n",
       "      <td>44.210000</td>\n",
       "      <td>734.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.665001</td>\n",
       "      <td>41.703951</td>\n",
       "      <td>45.011660</td>\n",
       "      <td>423.579580</td>\n",
       "      <td>0.285039</td>\n",
       "      <td>22.006802</td>\n",
       "      <td>5.992292</td>\n",
       "      <td>6.931119e+06</td>\n",
       "      <td>8.585311e+06</td>\n",
       "      <td>-87.203660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>7</td>\n",
       "      <td>2020/5/5 8:00:00</td>\n",
       "      <td>1.20</td>\n",
       "      <td>209.000000</td>\n",
       "      <td>90.4</td>\n",
       "      <td>51.357143</td>\n",
       "      <td>28.414286</td>\n",
       "      <td>20.228571</td>\n",
       "      <td>61.340000</td>\n",
       "      <td>725.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.501973</td>\n",
       "      <td>24.840552</td>\n",
       "      <td>42.000238</td>\n",
       "      <td>426.375415</td>\n",
       "      <td>0.284716</td>\n",
       "      <td>39.544856</td>\n",
       "      <td>3.175754</td>\n",
       "      <td>3.781119e+07</td>\n",
       "      <td>3.880701e+07</td>\n",
       "      <td>0.353919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>162</td>\n",
       "      <td>2018/8/3 8:00:00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>225.857143</td>\n",
       "      <td>90.0</td>\n",
       "      <td>52.500000</td>\n",
       "      <td>24.800000</td>\n",
       "      <td>22.700000</td>\n",
       "      <td>48.750000</td>\n",
       "      <td>729.700000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.494305</td>\n",
       "      <td>39.917584</td>\n",
       "      <td>38.998727</td>\n",
       "      <td>419.797903</td>\n",
       "      <td>0.279940</td>\n",
       "      <td>23.084806</td>\n",
       "      <td>5.667659</td>\n",
       "      <td>2.579016e+06</td>\n",
       "      <td>3.486488e+06</td>\n",
       "      <td>0.349456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>260</td>\n",
       "      <td>2017/9/13 8:00:00</td>\n",
       "      <td>1.21</td>\n",
       "      <td>302.142857</td>\n",
       "      <td>90.1</td>\n",
       "      <td>43.700000</td>\n",
       "      <td>32.310000</td>\n",
       "      <td>23.990000</td>\n",
       "      <td>48.580000</td>\n",
       "      <td>727.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.686798</td>\n",
       "      <td>43.702366</td>\n",
       "      <td>45.007534</td>\n",
       "      <td>425.429145</td>\n",
       "      <td>0.282122</td>\n",
       "      <td>23.182934</td>\n",
       "      <td>5.777419</td>\n",
       "      <td>7.852996e+06</td>\n",
       "      <td>9.864892e+06</td>\n",
       "      <td>-82.328429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>79</td>\n",
       "      <td>2019/8/23 8:00:00</td>\n",
       "      <td>1.68</td>\n",
       "      <td>214.000000</td>\n",
       "      <td>89.9</td>\n",
       "      <td>53.400000</td>\n",
       "      <td>24.950000</td>\n",
       "      <td>21.650000</td>\n",
       "      <td>62.227500</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.495965</td>\n",
       "      <td>53.185950</td>\n",
       "      <td>45.033543</td>\n",
       "      <td>425.576940</td>\n",
       "      <td>0.307664</td>\n",
       "      <td>34.296900</td>\n",
       "      <td>3.960256</td>\n",
       "      <td>2.306681e+07</td>\n",
       "      <td>2.737124e+07</td>\n",
       "      <td>0.353759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>234</td>\n",
       "      <td>2017/11/13 8:00:00</td>\n",
       "      <td>1.20</td>\n",
       "      <td>253.428571</td>\n",
       "      <td>90.3</td>\n",
       "      <td>49.420000</td>\n",
       "      <td>26.500000</td>\n",
       "      <td>24.080000</td>\n",
       "      <td>50.830000</td>\n",
       "      <td>723.700000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.665615</td>\n",
       "      <td>54.679364</td>\n",
       "      <td>44.973743</td>\n",
       "      <td>425.558722</td>\n",
       "      <td>0.283085</td>\n",
       "      <td>26.095561</td>\n",
       "      <td>5.242675</td>\n",
       "      <td>1.130741e+07</td>\n",
       "      <td>1.367624e+07</td>\n",
       "      <td>-66.676385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>243</td>\n",
       "      <td>2017/10/23 8:00:00</td>\n",
       "      <td>1.10</td>\n",
       "      <td>296.714286</td>\n",
       "      <td>89.9</td>\n",
       "      <td>47.540000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>22.060000</td>\n",
       "      <td>47.795000</td>\n",
       "      <td>733.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.645152</td>\n",
       "      <td>54.832588</td>\n",
       "      <td>44.954981</td>\n",
       "      <td>426.643265</td>\n",
       "      <td>0.281702</td>\n",
       "      <td>22.532015</td>\n",
       "      <td>5.904024</td>\n",
       "      <td>1.026734e+07</td>\n",
       "      <td>1.238208e+07</td>\n",
       "      <td>-72.064800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>248</td>\n",
       "      <td>2017/10/11 8:00:00</td>\n",
       "      <td>1.20</td>\n",
       "      <td>210.571429</td>\n",
       "      <td>90.4</td>\n",
       "      <td>44.280000</td>\n",
       "      <td>33.830000</td>\n",
       "      <td>21.890000</td>\n",
       "      <td>47.215000</td>\n",
       "      <td>730.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.667097</td>\n",
       "      <td>54.448861</td>\n",
       "      <td>44.994449</td>\n",
       "      <td>427.138347</td>\n",
       "      <td>0.291003</td>\n",
       "      <td>22.478547</td>\n",
       "      <td>6.171135</td>\n",
       "      <td>9.525680e+06</td>\n",
       "      <td>1.159183e+07</td>\n",
       "      <td>-75.143889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>309</td>\n",
       "      <td>2017/5/24 8:00:00</td>\n",
       "      <td>1.08</td>\n",
       "      <td>331.142857</td>\n",
       "      <td>89.4</td>\n",
       "      <td>46.760000</td>\n",
       "      <td>34.650000</td>\n",
       "      <td>18.590000</td>\n",
       "      <td>53.620000</td>\n",
       "      <td>716.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.673205</td>\n",
       "      <td>44.722796</td>\n",
       "      <td>49.910010</td>\n",
       "      <td>426.983037</td>\n",
       "      <td>0.287193</td>\n",
       "      <td>22.415456</td>\n",
       "      <td>5.818017</td>\n",
       "      <td>2.560704e+06</td>\n",
       "      <td>2.672689e+06</td>\n",
       "      <td>-111.066610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>35</td>\n",
       "      <td>2020/1/31 8:00:00</td>\n",
       "      <td>1.11</td>\n",
       "      <td>210.000000</td>\n",
       "      <td>88.7</td>\n",
       "      <td>54.514286</td>\n",
       "      <td>24.028571</td>\n",
       "      <td>21.457143</td>\n",
       "      <td>66.618571</td>\n",
       "      <td>724.771429</td>\n",
       "      <td>...</td>\n",
       "      <td>0.499210</td>\n",
       "      <td>87.171623</td>\n",
       "      <td>44.846628</td>\n",
       "      <td>427.331890</td>\n",
       "      <td>0.299236</td>\n",
       "      <td>37.174037</td>\n",
       "      <td>3.652880</td>\n",
       "      <td>3.149569e+07</td>\n",
       "      <td>3.572793e+07</td>\n",
       "      <td>0.349875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>51</td>\n",
       "      <td>2019/12/3 8:00:00</td>\n",
       "      <td>1.18</td>\n",
       "      <td>221.000000</td>\n",
       "      <td>89.6</td>\n",
       "      <td>59.500000</td>\n",
       "      <td>20.400000</td>\n",
       "      <td>20.100000</td>\n",
       "      <td>56.940000</td>\n",
       "      <td>726.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.487046</td>\n",
       "      <td>87.476091</td>\n",
       "      <td>42.995489</td>\n",
       "      <td>423.762480</td>\n",
       "      <td>0.300144</td>\n",
       "      <td>34.416345</td>\n",
       "      <td>3.944724</td>\n",
       "      <td>2.798938e+07</td>\n",
       "      <td>3.336984e+07</td>\n",
       "      <td>0.349539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>193</td>\n",
       "      <td>2018/3/19 8:00:00</td>\n",
       "      <td>1.51</td>\n",
       "      <td>307.285714</td>\n",
       "      <td>90.6</td>\n",
       "      <td>53.600000</td>\n",
       "      <td>25.900000</td>\n",
       "      <td>20.500000</td>\n",
       "      <td>58.110000</td>\n",
       "      <td>721.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.696024</td>\n",
       "      <td>36.078784</td>\n",
       "      <td>45.012439</td>\n",
       "      <td>429.609278</td>\n",
       "      <td>0.278845</td>\n",
       "      <td>26.597752</td>\n",
       "      <td>4.727231</td>\n",
       "      <td>1.726033e+07</td>\n",
       "      <td>2.117793e+07</td>\n",
       "      <td>-34.345942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>220</td>\n",
       "      <td>2018/1/15 8:00:00</td>\n",
       "      <td>0.92</td>\n",
       "      <td>261.857143</td>\n",
       "      <td>90.4</td>\n",
       "      <td>53.900000</td>\n",
       "      <td>22.300000</td>\n",
       "      <td>23.800000</td>\n",
       "      <td>55.260000</td>\n",
       "      <td>721.900000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.687531</td>\n",
       "      <td>52.050916</td>\n",
       "      <td>45.057809</td>\n",
       "      <td>428.992482</td>\n",
       "      <td>0.290619</td>\n",
       "      <td>31.054701</td>\n",
       "      <td>4.204469</td>\n",
       "      <td>1.437688e+07</td>\n",
       "      <td>1.738744e+07</td>\n",
       "      <td>-50.511166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>230</td>\n",
       "      <td>2017/12/22 8:00:00</td>\n",
       "      <td>1.32</td>\n",
       "      <td>181.000000</td>\n",
       "      <td>90.3</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>19.700000</td>\n",
       "      <td>21.300000</td>\n",
       "      <td>56.690000</td>\n",
       "      <td>722.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.689274</td>\n",
       "      <td>51.672012</td>\n",
       "      <td>45.012393</td>\n",
       "      <td>425.915498</td>\n",
       "      <td>0.286755</td>\n",
       "      <td>31.900262</td>\n",
       "      <td>4.192111</td>\n",
       "      <td>1.320927e+07</td>\n",
       "      <td>1.607255e+07</td>\n",
       "      <td>-56.669344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>242</td>\n",
       "      <td>2017/10/25 8:00:00</td>\n",
       "      <td>0.70</td>\n",
       "      <td>296.714286</td>\n",
       "      <td>90.1</td>\n",
       "      <td>47.540000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>22.060000</td>\n",
       "      <td>47.795000</td>\n",
       "      <td>733.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.647101</td>\n",
       "      <td>54.817995</td>\n",
       "      <td>44.956767</td>\n",
       "      <td>426.539975</td>\n",
       "      <td>0.281834</td>\n",
       "      <td>22.871400</td>\n",
       "      <td>5.841039</td>\n",
       "      <td>1.036639e+07</td>\n",
       "      <td>1.250534e+07</td>\n",
       "      <td>-71.551618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>276</td>\n",
       "      <td>2017/8/7 8:00:00</td>\n",
       "      <td>1.10</td>\n",
       "      <td>251.857143</td>\n",
       "      <td>89.9</td>\n",
       "      <td>47.100000</td>\n",
       "      <td>31.200000</td>\n",
       "      <td>21.700000</td>\n",
       "      <td>56.550000</td>\n",
       "      <td>725.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.667190</td>\n",
       "      <td>46.724935</td>\n",
       "      <td>44.999030</td>\n",
       "      <td>423.283303</td>\n",
       "      <td>0.291455</td>\n",
       "      <td>22.945624</td>\n",
       "      <td>6.042355</td>\n",
       "      <td>6.103093e+06</td>\n",
       "      <td>7.381752e+06</td>\n",
       "      <td>-91.822293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>255</td>\n",
       "      <td>2017/9/25 8:00:00</td>\n",
       "      <td>1.20</td>\n",
       "      <td>275.285714</td>\n",
       "      <td>90.0</td>\n",
       "      <td>51.800000</td>\n",
       "      <td>27.470000</td>\n",
       "      <td>20.730000</td>\n",
       "      <td>48.035000</td>\n",
       "      <td>724.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.678714</td>\n",
       "      <td>51.332360</td>\n",
       "      <td>44.896960</td>\n",
       "      <td>428.169748</td>\n",
       "      <td>0.289286</td>\n",
       "      <td>23.932692</td>\n",
       "      <td>5.665662</td>\n",
       "      <td>8.506657e+06</td>\n",
       "      <td>1.065132e+07</td>\n",
       "      <td>-79.249340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>261</td>\n",
       "      <td>2017/9/11 8:00:00</td>\n",
       "      <td>1.31</td>\n",
       "      <td>302.142857</td>\n",
       "      <td>89.9</td>\n",
       "      <td>43.700000</td>\n",
       "      <td>32.310000</td>\n",
       "      <td>23.990000</td>\n",
       "      <td>48.580000</td>\n",
       "      <td>727.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.671278</td>\n",
       "      <td>43.247926</td>\n",
       "      <td>44.989100</td>\n",
       "      <td>425.244285</td>\n",
       "      <td>0.288982</td>\n",
       "      <td>23.095806</td>\n",
       "      <td>5.962682</td>\n",
       "      <td>7.746927e+06</td>\n",
       "      <td>9.731510e+06</td>\n",
       "      <td>-82.841610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>306</td>\n",
       "      <td>2017/5/31 8:00:00</td>\n",
       "      <td>1.05</td>\n",
       "      <td>254.714286</td>\n",
       "      <td>90.8</td>\n",
       "      <td>43.240000</td>\n",
       "      <td>33.900000</td>\n",
       "      <td>22.860000</td>\n",
       "      <td>60.730000</td>\n",
       "      <td>724.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.672520</td>\n",
       "      <td>58.892811</td>\n",
       "      <td>46.585051</td>\n",
       "      <td>422.683515</td>\n",
       "      <td>0.285203</td>\n",
       "      <td>21.567433</td>\n",
       "      <td>5.970547</td>\n",
       "      <td>2.929400e+06</td>\n",
       "      <td>3.070111e+06</td>\n",
       "      <td>-109.270475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266</th>\n",
       "      <td>206</td>\n",
       "      <td>2018/2/16 8:00:00</td>\n",
       "      <td>1.31</td>\n",
       "      <td>310.714286</td>\n",
       "      <td>89.6</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>27.200000</td>\n",
       "      <td>22.300000</td>\n",
       "      <td>61.330000</td>\n",
       "      <td>724.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.691944</td>\n",
       "      <td>64.343791</td>\n",
       "      <td>44.928495</td>\n",
       "      <td>426.986445</td>\n",
       "      <td>0.292557</td>\n",
       "      <td>29.663963</td>\n",
       "      <td>4.651918</td>\n",
       "      <td>1.586589e+07</td>\n",
       "      <td>1.922201e+07</td>\n",
       "      <td>-42.300257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>267</th>\n",
       "      <td>304</td>\n",
       "      <td>2017/6/5 8:00:00</td>\n",
       "      <td>1.05</td>\n",
       "      <td>254.714286</td>\n",
       "      <td>90.0</td>\n",
       "      <td>43.240000</td>\n",
       "      <td>33.900000</td>\n",
       "      <td>22.860000</td>\n",
       "      <td>60.730000</td>\n",
       "      <td>724.300000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.684092</td>\n",
       "      <td>56.155798</td>\n",
       "      <td>42.012588</td>\n",
       "      <td>430.026372</td>\n",
       "      <td>0.283841</td>\n",
       "      <td>25.281172</td>\n",
       "      <td>5.089155</td>\n",
       "      <td>3.183513e+06</td>\n",
       "      <td>3.357317e+06</td>\n",
       "      <td>-107.987517</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>268 rows × 203 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     样本编号                  时间  RON损失    原料性质：硫含量  原料性质：辛烷值   原料性质：饱和烃  \\\n",
       "0       1   2020/5/26 8:00:00   1.38  188.000000      90.6  53.230000   \n",
       "1       2   2020/5/21 8:00:00   1.18  169.000000      90.5  52.300000   \n",
       "2       3   2020/5/19 8:00:00   1.38  177.000000      90.7  52.300000   \n",
       "3       4   2020/5/14 8:00:00   1.38  159.000000      90.4  52.300000   \n",
       "4       5   2020/5/12 8:00:00   1.28  173.000000      89.6  52.242857   \n",
       "5       6    2020/5/7 8:00:00   1.41  163.000000      91.0  52.100000   \n",
       "6       9   2020/4/29 8:00:00   1.10  165.000000      90.4  49.857143   \n",
       "7      10   2020/4/28 8:00:00   1.40  159.000000      90.2  50.214286   \n",
       "8      11   2020/4/23 8:00:00   1.30   85.000000      90.2  52.000000   \n",
       "9      12   2020/4/21 8:00:00   1.30  117.000000      90.2  53.000000   \n",
       "10     14   2020/4/14 8:00:00   1.40   83.000000      86.8  56.500000   \n",
       "11     15    2020/4/7 8:00:00   1.70  121.000000      87.8  55.700000   \n",
       "12     16    2020/4/3 8:00:00   1.70  115.000000      88.4  56.557143   \n",
       "13     18   2020/3/27 8:00:00   1.51  108.000000      88.0  56.342857   \n",
       "14     19   2020/3/25 8:24:26   1.11   98.170000      88.2  55.914286   \n",
       "15     20   2020/3/24 8:00:00   1.21  117.000000      88.8  55.700000   \n",
       "16     21   2020/3/19 8:19:04   1.51  111.000000      88.1  56.414286   \n",
       "17     22   2020/3/17 8:00:00   1.01   57.000000      88.2  56.700000   \n",
       "18     23   2020/3/13 8:00:00   1.61  148.000000      89.6  56.585714   \n",
       "19     24   2020/3/10 8:00:00   1.41  131.000000      89.0  56.500000   \n",
       "20     25    2020/3/6 8:00:00   1.41  222.000000      89.3  55.128571   \n",
       "21     26    2020/3/3 8:00:00   1.51  125.000000      89.2  54.100000   \n",
       "22     27   2020/2/28 8:00:00   1.41  156.000000      88.7  55.185714   \n",
       "23     28   2020/2/25 8:00:00   1.11  170.000000      89.0  56.000000   \n",
       "24     29   2020/2/21 8:00:00   1.41  206.000000      89.7  55.809524   \n",
       "25     30   2020/2/18 8:00:00   1.21  185.000000      89.2  55.666667   \n",
       "26     31   2020/2/14 8:00:00   1.71  172.000000      89.1  55.476190   \n",
       "27     32   2020/2/11 8:00:00   1.41  133.000000      88.5  55.333333   \n",
       "28     33    2020/2/7 8:00:00   1.11  189.000000      88.4  55.142857   \n",
       "29     34    2020/2/4 8:00:00   0.91  144.000000      88.1  55.000000   \n",
       "..    ...                 ...    ...         ...       ...        ...   \n",
       "238   302    2017/6/7 8:00:00   1.25  254.714286      90.4  43.240000   \n",
       "239   179   2018/6/25 8:00:00   0.54  231.428571      90.1  50.400000   \n",
       "240   227  2017/12/29 8:00:00   1.32  194.142857      90.5  55.800000   \n",
       "241   280   2017/7/28 8:00:00   1.15  206.428571      89.9  45.090000   \n",
       "242   320   2017/4/28 8:00:00   1.25  271.428571      89.5  47.190000   \n",
       "243    17   2020/3/31 8:00:00   1.10   77.000000      87.2  57.200000   \n",
       "244   278    2017/8/2 8:00:00   1.05  206.428571      89.5  45.090000   \n",
       "245   299   2017/6/14 8:00:00   1.15  245.000000      89.8  45.690000   \n",
       "246   108   2019/5/10 8:00:00   1.68  263.000000      90.6  50.400000   \n",
       "247   268   2017/8/25 8:00:00   1.34  300.714286      89.6  46.850000   \n",
       "248     7    2020/5/5 8:00:00   1.20  209.000000      90.4  51.357143   \n",
       "249   162    2018/8/3 8:00:00   1.21  225.857143      90.0  52.500000   \n",
       "250   260   2017/9/13 8:00:00   1.21  302.142857      90.1  43.700000   \n",
       "251    79   2019/8/23 8:00:00   1.68  214.000000      89.9  53.400000   \n",
       "252   234  2017/11/13 8:00:00   1.20  253.428571      90.3  49.420000   \n",
       "253   243  2017/10/23 8:00:00   1.10  296.714286      89.9  47.540000   \n",
       "254   248  2017/10/11 8:00:00   1.20  210.571429      90.4  44.280000   \n",
       "255   309   2017/5/24 8:00:00   1.08  331.142857      89.4  46.760000   \n",
       "256    35   2020/1/31 8:00:00   1.11  210.000000      88.7  54.514286   \n",
       "257    51   2019/12/3 8:00:00   1.18  221.000000      89.6  59.500000   \n",
       "258   193   2018/3/19 8:00:00   1.51  307.285714      90.6  53.600000   \n",
       "259   220   2018/1/15 8:00:00   0.92  261.857143      90.4  53.900000   \n",
       "260   230  2017/12/22 8:00:00   1.32  181.000000      90.3  59.000000   \n",
       "261   242  2017/10/25 8:00:00   0.70  296.714286      90.1  47.540000   \n",
       "262   276    2017/8/7 8:00:00   1.10  251.857143      89.9  47.100000   \n",
       "263   255   2017/9/25 8:00:00   1.20  275.285714      90.0  51.800000   \n",
       "264   261   2017/9/11 8:00:00   1.31  302.142857      89.9  43.700000   \n",
       "265   306   2017/5/31 8:00:00   1.05  254.714286      90.8  43.240000   \n",
       "266   206   2018/2/16 8:00:00   1.31  310.714286      89.6  50.500000   \n",
       "267   304    2017/6/5 8:00:00   1.05  254.714286      90.0  43.240000   \n",
       "\n",
       "       原料性质：烯烃    原料性质：芳烃    原料性质：溴值     原料性质：密度  ...  S-ZORB.AT-0011.DACA.PV  \\\n",
       "0    24.400000  22.370000  61.487143  726.085714  ...                0.496243   \n",
       "1    26.400000  21.300000  61.880000  731.300000  ...                0.491385   \n",
       "2    26.314286  21.385714  61.722857  729.614286  ...                0.495483   \n",
       "3    26.100000  21.600000  61.330000  725.400000  ...                0.490180   \n",
       "4    26.671429  21.085714  61.332857  725.428571  ...                0.501194   \n",
       "5    28.100000  19.800000  61.340000  725.500000  ...                0.491737   \n",
       "6    29.071429  21.071429  61.337143  725.442857  ...                0.494778   \n",
       "7    28.942857  20.842857  61.334286  725.385714  ...                0.501083   \n",
       "8    28.300000  19.700000  61.320000  725.100000  ...                0.497077   \n",
       "9    28.122222  18.877778  61.255556  723.522222  ...                0.491552   \n",
       "10   27.500000  16.000000  61.030000  718.000000  ...                0.491274   \n",
       "11   27.200000  17.100000  61.000000  715.100000  ...                0.493202   \n",
       "12   26.285714  17.157143  61.011429  716.300000  ...                0.497189   \n",
       "13   23.828571  19.828571  61.191429  719.600000  ...                0.497448   \n",
       "14   22.942857  21.142857  61.277143  720.800000  ...                0.672585   \n",
       "15   22.500000  21.800000  61.320000  721.400000  ...                0.498617   \n",
       "16   23.142857  20.442857  62.098571  722.257143  ...                0.503623   \n",
       "17   23.400000  19.900000  62.410000  722.600000  ...                0.499469   \n",
       "18   21.514286  21.900000  62.410000  722.600000  ...                0.491960   \n",
       "19   20.100000  23.400000  62.410000  722.600000  ...                0.488307   \n",
       "20   22.557143  22.314286  63.655714  723.742857  ...                0.487806   \n",
       "21   24.400000  21.500000  64.590000  724.600000  ...                0.493796   \n",
       "22   21.085714  23.728571  64.590000  724.600000  ...                0.493555   \n",
       "23   18.600000  25.400000  64.590000  724.600000  ...                0.493944   \n",
       "24   19.514286  24.676190  65.214762  724.676190  ...                0.491904   \n",
       "25   20.200000  24.133333  65.683333  724.733333  ...                0.493851   \n",
       "26   21.114286  23.409524  66.308095  724.809524  ...                0.493944   \n",
       "27   21.800000  22.866667  66.776667  724.866667  ...                0.493610   \n",
       "28   22.714286  22.142857  67.401429  724.942857  ...                0.487120   \n",
       "29   23.400000  21.600000  67.870000  725.000000  ...                0.502993   \n",
       "..         ...        ...        ...         ...  ...                     ...   \n",
       "238  33.900000  22.860000  60.730000  724.300000  ...                0.682904   \n",
       "239  23.400000  26.200000  43.820000  735.150000  ...                0.492326   \n",
       "240  24.000000  20.200000  56.900000  729.500000  ...                0.689663   \n",
       "241  31.040000  23.870000  55.730000  728.100000  ...                0.663027   \n",
       "242  31.300000  21.510000  52.020000  725.200000  ...                0.686593   \n",
       "243  25.600000  17.200000  61.020000  717.200000  ...                0.499377   \n",
       "244  31.040000  23.870000  55.730000  728.100000  ...                0.671899   \n",
       "245  34.670000  19.640000  58.000000  725.300000  ...                0.674468   \n",
       "246  27.200000  22.400000  52.282500  729.350000  ...                0.490921   \n",
       "247  30.490000  22.660000  44.210000  734.900000  ...                0.665001   \n",
       "248  28.414286  20.228571  61.340000  725.500000  ...                0.501973   \n",
       "249  24.800000  22.700000  48.750000  729.700000  ...                0.494305   \n",
       "250  32.310000  23.990000  48.580000  727.300000  ...                0.686798   \n",
       "251  24.950000  21.650000  62.227500  731.000000  ...                0.495965   \n",
       "252  26.500000  24.080000  50.830000  723.700000  ...                0.665615   \n",
       "253  30.400000  22.060000  47.795000  733.600000  ...                0.645152   \n",
       "254  33.830000  21.890000  47.215000  730.800000  ...                0.667097   \n",
       "255  34.650000  18.590000  53.620000  716.800000  ...                0.673205   \n",
       "256  24.028571  21.457143  66.618571  724.771429  ...                0.499210   \n",
       "257  20.400000  20.100000  56.940000  726.000000  ...                0.487046   \n",
       "258  25.900000  20.500000  58.110000  721.800000  ...                0.696024   \n",
       "259  22.300000  23.800000  55.260000  721.900000  ...                0.687531   \n",
       "260  19.700000  21.300000  56.690000  722.000000  ...                0.689274   \n",
       "261  30.400000  22.060000  47.795000  733.600000  ...                0.647101   \n",
       "262  31.200000  21.700000  56.550000  725.200000  ...                0.667190   \n",
       "263  27.470000  20.730000  48.035000  724.600000  ...                0.678714   \n",
       "264  32.310000  23.990000  48.580000  727.300000  ...                0.671278   \n",
       "265  33.900000  22.860000  60.730000  724.300000  ...                0.672520   \n",
       "266  27.200000  22.300000  61.330000  724.800000  ...                0.691944   \n",
       "267  33.900000  22.860000  60.730000  724.300000  ...                0.684092   \n",
       "\n",
       "     S-ZORB.FT_1204.DACA.PV  S-ZORB.LC_5102.PIDA.PV  S-ZORB.TE_1102.DACA.PV  \\\n",
       "0                 18.292067               42.015425              425.929515   \n",
       "1                 19.842605               40.903878              421.534365   \n",
       "2                 26.994896               42.103142              425.258420   \n",
       "3                 26.324458               41.970416              424.406195   \n",
       "4                 30.224367               42.900094              428.514740   \n",
       "5                 27.873024               42.006524              427.458155   \n",
       "6                 28.024165               42.003779              424.310965   \n",
       "7                 27.558598               42.011845              424.629485   \n",
       "8                 15.975918               41.852655              421.826745   \n",
       "9                 16.292095               41.990558              421.586110   \n",
       "10                24.858577               41.986386              423.489335   \n",
       "11                27.990915               42.023992              422.610860   \n",
       "12                20.698849               41.996880              426.063900   \n",
       "13                23.081207               42.007099              424.965160   \n",
       "14                25.365019               42.445853              423.928465   \n",
       "15                31.646892               42.005725              424.685800   \n",
       "16                54.421927               41.986496              424.651615   \n",
       "17                50.719780               41.961311              421.649090   \n",
       "18                77.720622               41.521537              426.130985   \n",
       "19                80.912347               41.977798              427.419780   \n",
       "20                92.197036               41.221145              427.982850   \n",
       "21                78.434768               42.694986              427.484970   \n",
       "22                79.476468               43.107891              425.670745   \n",
       "23                91.297853               39.701848              426.303780   \n",
       "24                82.058983               41.833351              426.015940   \n",
       "25                76.510345               39.432224              426.399895   \n",
       "26                76.105945               40.115808              424.573190   \n",
       "27                84.654931               41.033284              426.951155   \n",
       "28                84.296083               38.800305              427.027945   \n",
       "29                84.364933               42.461636              426.916015   \n",
       "..                      ...                     ...                     ...   \n",
       "238               31.515007               48.510241              425.907478   \n",
       "239               42.169189               38.995439              424.697885   \n",
       "240               34.457438               44.986011              428.322047   \n",
       "241               38.795700               44.989558              422.002772   \n",
       "242               28.237637               41.766124              421.294620   \n",
       "243               26.597893               41.995972              424.525475   \n",
       "244               45.121040               44.995582              423.088040   \n",
       "245               48.743563               41.764215              419.464813   \n",
       "246               70.023827               39.988794              425.348090   \n",
       "247               41.703951               45.011660              423.579580   \n",
       "248               24.840552               42.000238              426.375415   \n",
       "249               39.917584               38.998727              419.797903   \n",
       "250               43.702366               45.007534              425.429145   \n",
       "251               53.185950               45.033543              425.576940   \n",
       "252               54.679364               44.973743              425.558722   \n",
       "253               54.832588               44.954981              426.643265   \n",
       "254               54.448861               44.994449              427.138347   \n",
       "255               44.722796               49.910010              426.983037   \n",
       "256               87.171623               44.846628              427.331890   \n",
       "257               87.476091               42.995489              423.762480   \n",
       "258               36.078784               45.012439              429.609278   \n",
       "259               52.050916               45.057809              428.992482   \n",
       "260               51.672012               45.012393              425.915498   \n",
       "261               54.817995               44.956767              426.539975   \n",
       "262               46.724935               44.999030              423.283303   \n",
       "263               51.332360               44.896960              428.169748   \n",
       "264               43.247926               44.989100              425.244285   \n",
       "265               58.892811               46.585051              422.683515   \n",
       "266               64.343791               44.928495              426.986445   \n",
       "267               56.155798               42.012588              430.026372   \n",
       "\n",
       "     S-ZORB.CAL.LINE.PV  S-ZORB.CAL.CANGLIANG.PV  S-ZORB.CAL.SPEED.PV  \\\n",
       "0              0.282564                37.804650             3.324945   \n",
       "1              0.281381                37.876006             3.321169   \n",
       "2              0.282277                37.907927             3.319569   \n",
       "3              0.282275                39.177396             3.210211   \n",
       "4              0.282963                39.508370             3.178832   \n",
       "5              0.285585                39.458643             3.190527   \n",
       "6              0.284122                39.889699             3.147285   \n",
       "7              0.284169                39.948040             3.143236   \n",
       "8              0.277151                40.562405             2.977696   \n",
       "9              0.276983                40.618898             2.971716   \n",
       "10             0.277613                39.385355             3.064397   \n",
       "11             0.276967                37.064555             3.257477   \n",
       "12             0.277969                37.817228             3.195393   \n",
       "13             0.275221                36.948349             3.262378   \n",
       "14             0.281234                36.803149             3.414192   \n",
       "15             0.285215                36.573184             3.575398   \n",
       "16             0.285987                36.605458             3.568681   \n",
       "17             0.292024                35.751794             3.742808   \n",
       "18             0.292224                35.621330             3.749605   \n",
       "19             0.292619                35.711137             3.742039   \n",
       "20             0.293469                35.939728             3.720288   \n",
       "21             0.294629                35.545138             3.792150   \n",
       "22             0.294139                35.705946             3.772647   \n",
       "23             0.294642                35.860610             3.760765   \n",
       "24             0.294578                36.463434             3.695138   \n",
       "25             0.295632                35.716512             3.800442   \n",
       "26             0.296132                35.948945             3.779360   \n",
       "27             0.299715                36.842063             3.689150   \n",
       "28             0.298898                36.908064             3.679168   \n",
       "29             0.299187                37.099652             3.665850   \n",
       "..                  ...                      ...                  ...   \n",
       "238            0.285346                24.674995             5.204484   \n",
       "239            0.289957                24.325651             5.575779   \n",
       "240            0.278856                32.451271             3.960014   \n",
       "241            0.285701                22.418918             6.092723   \n",
       "242            0.292044                20.083964             6.547161   \n",
       "243            0.277341                37.682487             3.204449   \n",
       "244            0.296388                22.861628             6.241138   \n",
       "245            0.288439                23.565331             5.714073   \n",
       "246            0.312376                33.171430             4.089284   \n",
       "247            0.285039                22.006802             5.992292   \n",
       "248            0.284716                39.544856             3.175754   \n",
       "249            0.279940                23.084806             5.667659   \n",
       "250            0.282122                23.182934             5.777419   \n",
       "251            0.307664                34.296900             3.960256   \n",
       "252            0.283085                26.095561             5.242675   \n",
       "253            0.281702                22.532015             5.904024   \n",
       "254            0.291003                22.478547             6.171135   \n",
       "255            0.287193                22.415456             5.818017   \n",
       "256            0.299236                37.174037             3.652880   \n",
       "257            0.300144                34.416345             3.944724   \n",
       "258            0.278845                26.597752             4.727231   \n",
       "259            0.290619                31.054701             4.204469   \n",
       "260            0.286755                31.900262             4.192111   \n",
       "261            0.281834                22.871400             5.841039   \n",
       "262            0.291455                22.945624             6.042355   \n",
       "263            0.289286                23.932692             5.665662   \n",
       "264            0.288982                23.095806             5.962682   \n",
       "265            0.285203                21.567433             5.970547   \n",
       "266            0.292557                29.663963             4.651918   \n",
       "267            0.283841                25.281172             5.089155   \n",
       "\n",
       "     S-ZORB.FT_1503.TOTALIZERA.PV  S-ZORB.FT_1504.TOTALIZERA.PV  \\\n",
       "0                    3.906312e+07                  3.960876e+07   \n",
       "1                    3.881058e+07                  3.938930e+07   \n",
       "2                    3.869381e+07                  3.931262e+07   \n",
       "3                    3.841086e+07                  3.912020e+07   \n",
       "4                    3.828300e+07                  3.904595e+07   \n",
       "5                    3.794810e+07                  3.887028e+07   \n",
       "6                    3.743862e+07                  3.859890e+07   \n",
       "7                    3.737556e+07                  3.856812e+07   \n",
       "8                    3.704518e+07                  3.843288e+07   \n",
       "9                    3.691542e+07                  3.837698e+07   \n",
       "10                   3.647651e+07                  3.815302e+07   \n",
       "11                   3.606804e+07                  3.791104e+07   \n",
       "12                   3.581613e+07                  3.777479e+07   \n",
       "13                   3.534354e+07                  3.753607e+07   \n",
       "14                   3.522192e+07                  3.746738e+07   \n",
       "15                   3.515411e+07                  3.743258e+07   \n",
       "16                   3.480798e+07                  3.726364e+07   \n",
       "17                   3.467803e+07                  3.719708e+07   \n",
       "18                   3.440717e+07                  3.706533e+07   \n",
       "19                   3.419926e+07                  3.696766e+07   \n",
       "20                   3.391231e+07                  3.684692e+07   \n",
       "21                   3.369577e+07                  3.675443e+07   \n",
       "22                   3.341145e+07                  3.662938e+07   \n",
       "23                   3.319383e+07                  3.653298e+07   \n",
       "24                   3.291243e+07                  3.640393e+07   \n",
       "25                   3.270305e+07                  3.630571e+07   \n",
       "26                   3.242158e+07                  3.617385e+07   \n",
       "27                   3.222169e+07                  3.607842e+07   \n",
       "28                   3.195289e+07                  3.594744e+07   \n",
       "29                   3.175291e+07                  3.585419e+07   \n",
       "..                            ...                           ...   \n",
       "238                  3.296502e+06                  3.471070e+06   \n",
       "239                  7.480456e+05                  1.077253e+06   \n",
       "240                  1.351063e+07                  1.648705e+07   \n",
       "241                  5.608772e+06                  6.716107e+06   \n",
       "242                  1.617744e+06                  1.127116e+06   \n",
       "243                  3.561732e+07                  3.767269e+07   \n",
       "244                  5.859340e+06                  7.049883e+06   \n",
       "245                  3.675311e+06                  3.877717e+06   \n",
       "246                  1.757141e+07                  2.094580e+07   \n",
       "247                  6.931119e+06                  8.585311e+06   \n",
       "248                  3.781119e+07                  3.880701e+07   \n",
       "249                  2.579016e+06                  3.486488e+06   \n",
       "250                  7.852996e+06                  9.864892e+06   \n",
       "251                  2.306681e+07                  2.737124e+07   \n",
       "252                  1.130741e+07                  1.367624e+07   \n",
       "253                  1.026734e+07                  1.238208e+07   \n",
       "254                  9.525680e+06                  1.159183e+07   \n",
       "255                  2.560704e+06                  2.672689e+06   \n",
       "256                  3.149569e+07                  3.572793e+07   \n",
       "257                  2.798938e+07                  3.336984e+07   \n",
       "258                  1.726033e+07                  2.117793e+07   \n",
       "259                  1.437688e+07                  1.738744e+07   \n",
       "260                  1.320927e+07                  1.607255e+07   \n",
       "261                  1.036639e+07                  1.250534e+07   \n",
       "262                  6.103093e+06                  7.381752e+06   \n",
       "263                  8.506657e+06                  1.065132e+07   \n",
       "264                  7.746927e+06                  9.731510e+06   \n",
       "265                  2.929400e+06                  3.070111e+06   \n",
       "266                  1.586589e+07                  1.922201e+07   \n",
       "267                  3.183513e+06                  3.357317e+06   \n",
       "\n",
       "     S-ZORB.PC_1001A.PV  \n",
       "0              0.353271  \n",
       "1              0.354504  \n",
       "2              0.350181  \n",
       "3              0.353930  \n",
       "4              0.358053  \n",
       "5              0.350235  \n",
       "6              0.350821  \n",
       "7              0.340288  \n",
       "8              0.349968  \n",
       "9              0.350342  \n",
       "10             0.352959  \n",
       "11             0.347922  \n",
       "12             0.350079  \n",
       "13             0.350130  \n",
       "14             0.349789  \n",
       "15             0.349630  \n",
       "16             0.350443  \n",
       "17             0.349825  \n",
       "18             0.350634  \n",
       "19             0.350879  \n",
       "20             0.352470  \n",
       "21             0.349980  \n",
       "22             0.347576  \n",
       "23             0.350274  \n",
       "24             0.350299  \n",
       "25             0.350219  \n",
       "26             0.350573  \n",
       "27             0.350038  \n",
       "28             0.350214  \n",
       "29             0.352319  \n",
       "..                  ...  \n",
       "238         -107.474335  \n",
       "239           -9.200040  \n",
       "240          -54.873207  \n",
       "241          -94.388200  \n",
       "242         -117.737970  \n",
       "243            0.350337  \n",
       "244          -93.105246  \n",
       "245         -105.678200  \n",
       "246            0.350027  \n",
       "247          -87.203660  \n",
       "248            0.353919  \n",
       "249            0.349456  \n",
       "250          -82.328429  \n",
       "251            0.353759  \n",
       "252          -66.676385  \n",
       "253          -72.064800  \n",
       "254          -75.143889  \n",
       "255         -111.066610  \n",
       "256            0.349875  \n",
       "257            0.349539  \n",
       "258          -34.345942  \n",
       "259          -50.511166  \n",
       "260          -56.669344  \n",
       "261          -71.551618  \n",
       "262          -91.822293  \n",
       "263          -79.249340  \n",
       "264          -82.841610  \n",
       "265         -109.270475  \n",
       "266          -42.300257  \n",
       "267         -107.987517  \n",
       "\n",
       "[268 rows x 203 columns]"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_325"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_325 = data_325.sort_values(by=\"RON损失\" , ascending=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>样本编号</th>\n",
       "      <th>时间</th>\n",
       "      <th>RON损失</th>\n",
       "      <th>原料性质：硫含量</th>\n",
       "      <th>原料性质：辛烷值</th>\n",
       "      <th>原料性质：饱和烃</th>\n",
       "      <th>原料性质：烯烃</th>\n",
       "      <th>原料性质：芳烃</th>\n",
       "      <th>原料性质：溴值</th>\n",
       "      <th>原料性质：密度</th>\n",
       "      <th>产品性质：硫含量</th>\n",
       "      <th>产品性质：辛烷值</th>\n",
       "      <th>待生吸附剂性质：焦炭</th>\n",
       "      <th>待生吸附剂性质：S</th>\n",
       "      <th>再生吸附剂性质：焦炭</th>\n",
       "      <th>再生吸附剂性质：S</th>\n",
       "      <th>S-ZORB.CAL_H2.PV</th>\n",
       "      <th>S-ZORB.PDI_2102.PV</th>\n",
       "      <th>S-ZORB.PT_2801.PV</th>\n",
       "      <th>S-ZORB.FC_2801.PV</th>\n",
       "      <th>S-ZORB.TE_2103.PV</th>\n",
       "      <th>S-ZORB.TE_2005.PV</th>\n",
       "      <th>S-ZORB.PT_2101.PV</th>\n",
       "      <th>S-ZORB.PDT_2104.PV</th>\n",
       "      <th>S-ZORB.TE_2301.PV</th>\n",
       "      <th>S-ZORB.PT_2301.PV</th>\n",
       "      <th>S-ZORB.PC_2105.PV</th>\n",
       "      <th>S-ZORB.PC_5101.PV</th>\n",
       "      <th>S-ZORB.TC_5005.PV</th>\n",
       "      <th>S-ZORB.LC_5001.PV</th>\n",
       "      <th>S-ZORB.LC_5101.PV</th>\n",
       "      <th>S-ZORB.TE_5102.PV</th>\n",
       "      <th>S-ZORB.TE_5202.PV</th>\n",
       "      <th>S-ZORB.FT_5101.PV</th>\n",
       "      <th>S-ZORB.TE_9001.PV</th>\n",
       "      <th>S-ZORB.FT_9001.PV</th>\n",
       "      <th>S-ZORB.FT_9403.PV</th>\n",
       "      <th>S-ZORB.PT_9403.PV</th>\n",
       "      <th>S-ZORB.TE_9301.PV</th>\n",
       "      <th>S-ZORB.FT_9202.PV</th>\n",
       "      <th>S-ZORB.FT_9302.PV</th>\n",
       "      <th>S-ZORB.FT_3301.PV</th>\n",
       "      <th>S-ZORB.FT_9402.PV</th>\n",
       "      <th>S-ZORB.PT_9402.PV</th>\n",
       "      <th>S-ZORB.PT_9401.PV</th>\n",
       "      <th>S-ZORB.PDC_2502.PV</th>\n",
       "      <th>S-ZORB.FC_1005.PV</th>\n",
       "      <th>S-ZORB.FC_1102.PV</th>\n",
       "      <th>S-ZORB.TE_1105.PV</th>\n",
       "      <th>S-ZORB.PDI_1102.PV</th>\n",
       "      <th>S-ZORB.TE_1601.PV</th>\n",
       "      <th>S-ZORB.AC_6001.PV</th>\n",
       "      <th>S-ZORB.TE_1608.PV</th>\n",
       "      <th>S-ZORB.PT_6002.PV</th>\n",
       "      <th>S-ZORB.PC_1603.PV</th>\n",
       "      <th>S-ZORB.PT_1602A.PV</th>\n",
       "      <th>S-ZORB.PC_1301.PV</th>\n",
       "      <th>S-ZORB.PT_1201.PV</th>\n",
       "      <th>S-ZORB.TE_1201.PV</th>\n",
       "      <th>S-ZORB.TE_1203.PV</th>\n",
       "      <th>S-ZORB.PC_1202.PV</th>\n",
       "      <th>S-ZORB.TC_2801.PV</th>\n",
       "      <th>S-ZORB.FC_2601.PV</th>\n",
       "      <th>S-ZORB.PDT_2604.PV</th>\n",
       "      <th>S-ZORB.TE_2601.PV</th>\n",
       "      <th>S-ZORB.TC_2607.PV</th>\n",
       "      <th>S-ZORB.PDI_2703A.PV</th>\n",
       "      <th>S-ZORB.PT_1501.PV</th>\n",
       "      <th>S-ZORB.FT_9001.TOTAL</th>\n",
       "      <th>S-ZORB.FT_5201.TOTAL</th>\n",
       "      <th>S-ZORB.FT_5101.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9101.TOTAL</th>\n",
       "      <th>S-ZORB.FT_3301.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9201.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9202.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9301.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9302.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9401.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9402.TOTAL</th>\n",
       "      <th>S-ZORB.FT_9403.TOTAL</th>\n",
       "      <th>S-ZORB.FC_1101.TOTAL</th>\n",
       "      <th>S-ZORB.FT_1204.TOTAL</th>\n",
       "      <th>S-ZORB.FT_1001.TOTAL</th>\n",
       "      <th>S-ZORB.TE_1101.DACA</th>\n",
       "      <th>S-ZORB.PT_1102.DACA</th>\n",
       "      <th>S-ZORB.PT_1103.DACA</th>\n",
       "      <th>S-ZORB.TE_1106.DACA</th>\n",
       "      <th>S-ZORB.LI_9102.DACA</th>\n",
       "      <th>S-ZORB.TE_9003.DACA</th>\n",
       "      <th>S-ZORB.TE_9002.DACA</th>\n",
       "      <th>S-ZORB.PC_9002.DACA</th>\n",
       "      <th>S-ZORB.LC_5102.DACA</th>\n",
       "      <th>S-ZORB.LT_3801.DACA</th>\n",
       "      <th>S-ZORB.LT_3101.DACA</th>\n",
       "      <th>S-ZORB.PC_3101.DACA</th>\n",
       "      <th>S-ZORB.TE_3101.DACA</th>\n",
       "      <th>S-ZORB.FT_3303.DACA</th>\n",
       "      <th>S-ZORB.TE_1501.DACA</th>\n",
       "      <th>S-ZORB.TE_1502.DACA</th>\n",
       "      <th>S-ZORB.LT_2101.DACA</th>\n",
       "      <th>S-ZORB.FT_2701.DACA</th>\n",
       "      <th>S-ZORB.FC_2702.DACA</th>\n",
       "      <th>S-ZORB.TC_2702.DACA</th>\n",
       "      <th>S-ZORB.LT_2901.DACA</th>\n",
       "      <th>S-ZORB.TE_2901.DACA</th>\n",
       "      <th>S-ZORB.TE_2902.DACA</th>\n",
       "      <th>S-ZORB.TE_2501.DACA</th>\n",
       "      <th>S-ZORB.PT_2501.DACA</th>\n",
       "      <th>S-ZORB.PT_2502.DACA</th>\n",
       "      <th>S-ZORB.FT_2433.DACA</th>\n",
       "      <th>S-ZORB.TE_2401.DACA</th>\n",
       "      <th>S-ZORB.SIS_TE_2802</th>\n",
       "      <th>S-ZORB.TE_5002.DACA</th>\n",
       "      <th>S-ZORB.TE_5004.DACA</th>\n",
       "      <th>S-ZORB.TE_5006.DACA</th>\n",
       "      <th>S-ZORB.TE_5003.DACA</th>\n",
       "      <th>S-ZORB.TE_5201.DACA</th>\n",
       "      <th>S-ZORB.TE_5101.DACA</th>\n",
       "      <th>S-ZORB.FT_2431.DACA</th>\n",
       "      <th>S-ZORB.SIS_TE_2606.PV</th>\n",
       "      <th>S-ZORB.SIS_TE_2605.PV</th>\n",
       "      <th>S-ZORB.PDT_2704.DACA</th>\n",
       "      <th>S-ZORB.PDC_2702.DACA</th>\n",
       "      <th>S-ZORB.PT_6009.DACA</th>\n",
       "      <th>S-ZORB.LI_2104.DACA</th>\n",
       "      <th>S-ZORB.TE_6002.DACA</th>\n",
       "      <th>S-ZORB.TE_6001.DACA</th>\n",
       "      <th>S-ZORB.PT_1101.DACA</th>\n",
       "      <th>S-ZORB.FC_5103.DACA</th>\n",
       "      <th>S-ZORB.PDT_3601.DACA</th>\n",
       "      <th>S-ZORB.PT_6006.DACA</th>\n",
       "      <th>S-ZORB.SIS_TE_6009.PV</th>\n",
       "      <th>S-ZORB.SIS_PT_6007.PV</th>\n",
       "      <th>S-ZORB.TE_6008.DACA</th>\n",
       "      <th>S-ZORB.PT_5201.DACA</th>\n",
       "      <th>S-ZORB.PC_3501.DACA</th>\n",
       "      <th>S-ZORB.LT_9101.DACA</th>\n",
       "      <th>S-ZORB.PT_6003.DACA</th>\n",
       "      <th>S-ZORB.PDI_2105.DACA</th>\n",
       "      <th>S-ZORB.BS_LT_2401.PV</th>\n",
       "      <th>S-ZORB.FT_3701.DACA</th>\n",
       "      <th>S-ZORB.PT_2603.DACA</th>\n",
       "      <th>S-ZORB.PDT_2606.DACA</th>\n",
       "      <th>S-ZORB.ZT_2634.DACA</th>\n",
       "      <th>S-ZORB.TE_2603.DACA</th>\n",
       "      <th>S-ZORB.TE_2604.DACA</th>\n",
       "      <th>S-ZORB.TE_2104.DACA</th>\n",
       "      <th>S-ZORB.PDT_2001.DACA</th>\n",
       "      <th>S-ZORB.TE_2002.DACA</th>\n",
       "      <th>S-ZORB.TE_2004.DACA</th>\n",
       "      <th>S-ZORB.TE_2003.DACA</th>\n",
       "      <th>S-ZORB.PDT_1003.DACA</th>\n",
       "      <th>S-ZORB.PDT_1002.DACA</th>\n",
       "      <th>S-ZORB.PDT_3503.DACA</th>\n",
       "      <th>S-ZORB.PDT_3502.DACA</th>\n",
       "      <th>S-ZORB.PDT_3002.DACA</th>\n",
       "      <th>S-ZORB.PDT_1004.DACA</th>\n",
       "      <th>S-ZORB.PDI_2903.DACA</th>\n",
       "      <th>S-ZORB.PT_2901.DACA</th>\n",
       "      <th>S-ZORB.PT_2106.DACA</th>\n",
       "      <th>S-ZORB.TE_7508B.DACA</th>\n",
       "      <th>S-ZORB.TE_7506B.DACA</th>\n",
       "      <th>S-ZORB.PT_7505B.DACA</th>\n",
       "      <th>S-ZORB.TE_7504B.DACA</th>\n",
       "      <th>S-ZORB.PT_7503B.DACA</th>\n",
       "      <th>S-ZORB.TE_7502B.DACA</th>\n",
       "      <th>S-ZORB.TE_7106B.DACA</th>\n",
       "      <th>S-ZORB.TE_7108B.DACA</th>\n",
       "      <th>S-ZORB.PT_7107B.DACA</th>\n",
       "      <th>S-ZORB.PT_7103B.DACA</th>\n",
       "      <th>S-ZORB.PT_1604.DACA</th>\n",
       "      <th>S-ZORB.TC_1607.DACA</th>\n",
       "      <th>S-ZORB.PT_6005.DACA</th>\n",
       "      <th>S-ZORB.PT_6008.DACA</th>\n",
       "      <th>S-ZORB.PT_1601.DACA</th>\n",
       "      <th>S-ZORB.TE_1605.DACA</th>\n",
       "      <th>S-ZORB.SIS_FT_3202.PV</th>\n",
       "      <th>S-ZORB.TXE_3202A.DACA</th>\n",
       "      <th>S-ZORB.TXE_3201A.DACA</th>\n",
       "      <th>S-ZORB.TXE_2203A.DACA</th>\n",
       "      <th>S-ZORB.TXE_2202A.DACA</th>\n",
       "      <th>S-ZORB.TE_5008.DACA</th>\n",
       "      <th>S-ZORB.TE_5009.DACA</th>\n",
       "      <th>S-ZORB.FC_5001.DACA</th>\n",
       "      <th>S-ZORB.TE_1503.DACA</th>\n",
       "      <th>S-ZORB.AT-0001.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0002.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0004.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0005.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0006.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0007.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0008.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0009.DACA.PV</th>\n",
       "      <th>S-ZORB.AT-0011.DACA.PV</th>\n",
       "      <th>S-ZORB.FT_1204.DACA.PV</th>\n",
       "      <th>S-ZORB.LC_5102.PIDA.PV</th>\n",
       "      <th>S-ZORB.TE_1102.DACA.PV</th>\n",
       "      <th>S-ZORB.CAL.LINE.PV</th>\n",
       "      <th>S-ZORB.CAL.CANGLIANG.PV</th>\n",
       "      <th>S-ZORB.CAL.SPEED.PV</th>\n",
       "      <th>S-ZORB.FT_1503.TOTALIZERA.PV</th>\n",
       "      <th>S-ZORB.FT_1504.TOTALIZERA.PV</th>\n",
       "      <th>S-ZORB.PC_1001A.PV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>142</td>\n",
       "      <td>2019/1/18 8:00:00</td>\n",
       "      <td>0.20</td>\n",
       "      <td>153.428571</td>\n",
       "      <td>85.3</td>\n",
       "      <td>58.50</td>\n",
       "      <td>17.6</td>\n",
       "      <td>23.90</td>\n",
       "      <td>45.150</td>\n",
       "      <td>720.80</td>\n",
       "      <td>3.2</td>\n",
       "      <td>85.10</td>\n",
       "      <td>2.45</td>\n",
       "      <td>8.85</td>\n",
       "      <td>1.27</td>\n",
       "      <td>6.69</td>\n",
       "      <td>0.302291</td>\n",
       "      <td>23.189189</td>\n",
       "      <td>2.467430</td>\n",
       "      <td>652.255985</td>\n",
       "      <td>421.857275</td>\n",
       "      <td>415.880212</td>\n",
       "      <td>2.354010</td>\n",
       "      <td>81.158234</td>\n",
       "      <td>374.109665</td>\n",
       "      <td>2.366296</td>\n",
       "      <td>4.795737</td>\n",
       "      <td>0.660073</td>\n",
       "      <td>118.851450</td>\n",
       "      <td>55.040801</td>\n",
       "      <td>49.987329</td>\n",
       "      <td>25.588707</td>\n",
       "      <td>34.683582</td>\n",
       "      <td>737.834190</td>\n",
       "      <td>17.345706</td>\n",
       "      <td>466.062710</td>\n",
       "      <td>567.702378</td>\n",
       "      <td>0.992984</td>\n",
       "      <td>205.330502</td>\n",
       "      <td>425.288772</td>\n",
       "      <td>4603.358500</td>\n",
       "      <td>251.303697</td>\n",
       "      <td>358.665613</td>\n",
       "      <td>0.629209</td>\n",
       "      <td>0.547578</td>\n",
       "      <td>19.074767</td>\n",
       "      <td>140.109633</td>\n",
       "      <td>8665.056575</td>\n",
       "      <td>47.826013</td>\n",
       "      <td>0.162193</td>\n",
       "      <td>363.093860</td>\n",
       "      <td>2.003106</td>\n",
       "      <td>440.924715</td>\n",
       "      <td>-0.246122</td>\n",
       "      <td>0.051094</td>\n",
       "      <td>0.382390</td>\n",
       "      <td>3.054283</td>\n",
       "      <td>2.271794</td>\n",
       "      <td>113.701678</td>\n",
       "      <td>28.601333</td>\n",
       "      <td>2.251315</td>\n",
       "      <td>269.784730</td>\n",
       "      <td>74.025252</td>\n",
       "      <td>37.942943</td>\n",
       "      <td>270.117948</td>\n",
       "      <td>505.343350</td>\n",
       "      <td>33.569865</td>\n",
       "      <td>1.968169</td>\n",
       "      <td>2.860659e+06</td>\n",
       "      <td>7.071382e+05</td>\n",
       "      <td>5.852788e+06</td>\n",
       "      <td>1394.796000</td>\n",
       "      <td>1689.491550</td>\n",
       "      <td>2.660594e+06</td>\n",
       "      <td>2.415157e+06</td>\n",
       "      <td>6143.337925</td>\n",
       "      <td>18733.112000</td>\n",
       "      <td>6.879282e+05</td>\n",
       "      <td>3.082328e+06</td>\n",
       "      <td>3.151981e+06</td>\n",
       "      <td>7.303289e+05</td>\n",
       "      <td>174935.690</td>\n",
       "      <td>6.718409e+05</td>\n",
       "      <td>115.515807</td>\n",
       "      <td>2.678865</td>\n",
       "      <td>2.516416</td>\n",
       "      <td>122.803100</td>\n",
       "      <td>54.138311</td>\n",
       "      <td>17.709174</td>\n",
       "      <td>33.382268</td>\n",
       "      <td>0.383522</td>\n",
       "      <td>40.019718</td>\n",
       "      <td>0.718196</td>\n",
       "      <td>-1.278075</td>\n",
       "      <td>0.399145</td>\n",
       "      <td>7.677337</td>\n",
       "      <td>170.176559</td>\n",
       "      <td>21.954300</td>\n",
       "      <td>9.111824</td>\n",
       "      <td>-1.340856</td>\n",
       "      <td>15.306804</td>\n",
       "      <td>41.307959</td>\n",
       "      <td>260.493843</td>\n",
       "      <td>30.705983</td>\n",
       "      <td>13.933394</td>\n",
       "      <td>15.015881</td>\n",
       "      <td>232.452760</td>\n",
       "      <td>0.145637</td>\n",
       "      <td>0.160647</td>\n",
       "      <td>5.402442</td>\n",
       "      <td>323.749950</td>\n",
       "      <td>271.326315</td>\n",
       "      <td>110.942325</td>\n",
       "      <td>54.271912</td>\n",
       "      <td>131.747580</td>\n",
       "      <td>62.882536</td>\n",
       "      <td>64.592642</td>\n",
       "      <td>44.430071</td>\n",
       "      <td>492.527505</td>\n",
       "      <td>502.677805</td>\n",
       "      <td>501.299860</td>\n",
       "      <td>33.422755</td>\n",
       "      <td>24.616618</td>\n",
       "      <td>1.142250</td>\n",
       "      <td>30.279219</td>\n",
       "      <td>735.242415</td>\n",
       "      <td>375.336275</td>\n",
       "      <td>3.053792</td>\n",
       "      <td>9689.481200</td>\n",
       "      <td>0.089603</td>\n",
       "      <td>-0.762954</td>\n",
       "      <td>297.487037</td>\n",
       "      <td>-1124.399725</td>\n",
       "      <td>267.230527</td>\n",
       "      <td>0.624863</td>\n",
       "      <td>3.012523</td>\n",
       "      <td>7.467458</td>\n",
       "      <td>-0.049358</td>\n",
       "      <td>2.831036</td>\n",
       "      <td>29.827915</td>\n",
       "      <td>39.468163</td>\n",
       "      <td>0.146417</td>\n",
       "      <td>11.204336</td>\n",
       "      <td>42.411540</td>\n",
       "      <td>424.709835</td>\n",
       "      <td>500.387162</td>\n",
       "      <td>423.928120</td>\n",
       "      <td>27.303293</td>\n",
       "      <td>417.029705</td>\n",
       "      <td>415.446300</td>\n",
       "      <td>413.883400</td>\n",
       "      <td>8.833203</td>\n",
       "      <td>1.592630</td>\n",
       "      <td>0.414316</td>\n",
       "      <td>10.840374</td>\n",
       "      <td>1.859845</td>\n",
       "      <td>16.262325</td>\n",
       "      <td>6.654529</td>\n",
       "      <td>545.758200</td>\n",
       "      <td>4.792891</td>\n",
       "      <td>7.413568</td>\n",
       "      <td>5.315188</td>\n",
       "      <td>0.079719</td>\n",
       "      <td>7.140621</td>\n",
       "      <td>0.081644</td>\n",
       "      <td>5.474902</td>\n",
       "      <td>52.090584</td>\n",
       "      <td>49.613284</td>\n",
       "      <td>3.075745</td>\n",
       "      <td>2.237385</td>\n",
       "      <td>0.179700</td>\n",
       "      <td>432.457522</td>\n",
       "      <td>-0.221964</td>\n",
       "      <td>-0.139021</td>\n",
       "      <td>2.449868</td>\n",
       "      <td>409.125185</td>\n",
       "      <td>183.725845</td>\n",
       "      <td>358.456310</td>\n",
       "      <td>400.895607</td>\n",
       "      <td>484.919692</td>\n",
       "      <td>486.014535</td>\n",
       "      <td>69.642916</td>\n",
       "      <td>17.145213</td>\n",
       "      <td>2482.262175</td>\n",
       "      <td>7.386963</td>\n",
       "      <td>4.053312</td>\n",
       "      <td>5.799679</td>\n",
       "      <td>0.459793</td>\n",
       "      <td>0.525555</td>\n",
       "      <td>0.479819</td>\n",
       "      <td>0.470983</td>\n",
       "      <td>0.430031</td>\n",
       "      <td>0.471771</td>\n",
       "      <td>0.489661</td>\n",
       "      <td>75.141766</td>\n",
       "      <td>40.011234</td>\n",
       "      <td>423.929697</td>\n",
       "      <td>0.313991</td>\n",
       "      <td>30.271820</td>\n",
       "      <td>4.485089</td>\n",
       "      <td>1.201823e+07</td>\n",
       "      <td>13658326.50</td>\n",
       "      <td>0.349741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>179</td>\n",
       "      <td>2018/6/25 8:00:00</td>\n",
       "      <td>0.54</td>\n",
       "      <td>231.428571</td>\n",
       "      <td>90.1</td>\n",
       "      <td>50.40</td>\n",
       "      <td>23.4</td>\n",
       "      <td>26.20</td>\n",
       "      <td>43.820</td>\n",
       "      <td>735.15</td>\n",
       "      <td>4.3</td>\n",
       "      <td>89.56</td>\n",
       "      <td>3.48</td>\n",
       "      <td>10.67</td>\n",
       "      <td>0.90</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.232117</td>\n",
       "      <td>17.440714</td>\n",
       "      <td>2.504474</td>\n",
       "      <td>651.170082</td>\n",
       "      <td>423.964413</td>\n",
       "      <td>420.478555</td>\n",
       "      <td>2.401949</td>\n",
       "      <td>65.193053</td>\n",
       "      <td>306.001070</td>\n",
       "      <td>2.414110</td>\n",
       "      <td>4.798732</td>\n",
       "      <td>0.660179</td>\n",
       "      <td>128.249900</td>\n",
       "      <td>46.019762</td>\n",
       "      <td>556.221002</td>\n",
       "      <td>33.124049</td>\n",
       "      <td>36.897491</td>\n",
       "      <td>1254.662175</td>\n",
       "      <td>29.282571</td>\n",
       "      <td>540.493378</td>\n",
       "      <td>556.221002</td>\n",
       "      <td>0.994322</td>\n",
       "      <td>206.939877</td>\n",
       "      <td>441.412810</td>\n",
       "      <td>1034.989777</td>\n",
       "      <td>368.400145</td>\n",
       "      <td>740.214717</td>\n",
       "      <td>0.615811</td>\n",
       "      <td>0.514686</td>\n",
       "      <td>27.185475</td>\n",
       "      <td>144.708300</td>\n",
       "      <td>6082.223150</td>\n",
       "      <td>68.908238</td>\n",
       "      <td>0.125474</td>\n",
       "      <td>362.785255</td>\n",
       "      <td>2.298722</td>\n",
       "      <td>455.054298</td>\n",
       "      <td>-0.190461</td>\n",
       "      <td>0.049344</td>\n",
       "      <td>0.380161</td>\n",
       "      <td>3.001516</td>\n",
       "      <td>2.331590</td>\n",
       "      <td>139.093382</td>\n",
       "      <td>34.648286</td>\n",
       "      <td>2.299057</td>\n",
       "      <td>298.292110</td>\n",
       "      <td>80.214898</td>\n",
       "      <td>42.621959</td>\n",
       "      <td>282.123227</td>\n",
       "      <td>487.105630</td>\n",
       "      <td>32.826797</td>\n",
       "      <td>1.544113</td>\n",
       "      <td>3.517421e+05</td>\n",
       "      <td>8.551135e+04</td>\n",
       "      <td>7.416220e+05</td>\n",
       "      <td>486.466615</td>\n",
       "      <td>219.030810</td>\n",
       "      <td>5.113878e+05</td>\n",
       "      <td>3.110871e+05</td>\n",
       "      <td>586.456920</td>\n",
       "      <td>660.774940</td>\n",
       "      <td>1.392635e+05</td>\n",
       "      <td>4.536035e+05</td>\n",
       "      <td>4.133201e+05</td>\n",
       "      <td>8.822381e+04</td>\n",
       "      <td>2076359.375</td>\n",
       "      <td>8.420167e+04</td>\n",
       "      <td>141.161082</td>\n",
       "      <td>2.703914</td>\n",
       "      <td>2.578487</td>\n",
       "      <td>164.783845</td>\n",
       "      <td>87.324372</td>\n",
       "      <td>29.001526</td>\n",
       "      <td>31.734695</td>\n",
       "      <td>0.380075</td>\n",
       "      <td>38.993849</td>\n",
       "      <td>-0.171501</td>\n",
       "      <td>-1.266395</td>\n",
       "      <td>0.399001</td>\n",
       "      <td>26.482363</td>\n",
       "      <td>290.059087</td>\n",
       "      <td>22.419811</td>\n",
       "      <td>27.093236</td>\n",
       "      <td>-1.290769</td>\n",
       "      <td>58.026285</td>\n",
       "      <td>29.014827</td>\n",
       "      <td>260.082595</td>\n",
       "      <td>22.860594</td>\n",
       "      <td>30.915094</td>\n",
       "      <td>32.578755</td>\n",
       "      <td>211.554955</td>\n",
       "      <td>0.155537</td>\n",
       "      <td>0.172283</td>\n",
       "      <td>4.737708</td>\n",
       "      <td>265.687587</td>\n",
       "      <td>299.148343</td>\n",
       "      <td>132.893435</td>\n",
       "      <td>51.695513</td>\n",
       "      <td>139.064222</td>\n",
       "      <td>55.503849</td>\n",
       "      <td>55.931638</td>\n",
       "      <td>46.354386</td>\n",
       "      <td>269.510851</td>\n",
       "      <td>484.222753</td>\n",
       "      <td>484.574435</td>\n",
       "      <td>33.122203</td>\n",
       "      <td>31.642861</td>\n",
       "      <td>1.025846</td>\n",
       "      <td>24.321275</td>\n",
       "      <td>757.227392</td>\n",
       "      <td>381.810445</td>\n",
       "      <td>2.995656</td>\n",
       "      <td>7538.660150</td>\n",
       "      <td>0.101576</td>\n",
       "      <td>-0.771467</td>\n",
       "      <td>307.853712</td>\n",
       "      <td>-1154.638450</td>\n",
       "      <td>280.822052</td>\n",
       "      <td>0.570104</td>\n",
       "      <td>2.959342</td>\n",
       "      <td>2.255373</td>\n",
       "      <td>-0.071439</td>\n",
       "      <td>3.254476</td>\n",
       "      <td>29.485272</td>\n",
       "      <td>34.618066</td>\n",
       "      <td>0.151099</td>\n",
       "      <td>10.017687</td>\n",
       "      <td>52.215769</td>\n",
       "      <td>446.566818</td>\n",
       "      <td>482.373215</td>\n",
       "      <td>424.751535</td>\n",
       "      <td>24.347757</td>\n",
       "      <td>420.892835</td>\n",
       "      <td>419.781605</td>\n",
       "      <td>418.049318</td>\n",
       "      <td>10.232166</td>\n",
       "      <td>1.619074</td>\n",
       "      <td>-0.046673</td>\n",
       "      <td>12.297529</td>\n",
       "      <td>0.857222</td>\n",
       "      <td>2.624593</td>\n",
       "      <td>6.405130</td>\n",
       "      <td>547.978245</td>\n",
       "      <td>4.803425</td>\n",
       "      <td>25.911597</td>\n",
       "      <td>25.492286</td>\n",
       "      <td>0.176029</td>\n",
       "      <td>25.668823</td>\n",
       "      <td>0.175327</td>\n",
       "      <td>25.586272</td>\n",
       "      <td>26.584718</td>\n",
       "      <td>26.713832</td>\n",
       "      <td>2.274992</td>\n",
       "      <td>2.269821</td>\n",
       "      <td>0.173732</td>\n",
       "      <td>449.576323</td>\n",
       "      <td>-0.175249</td>\n",
       "      <td>-0.073258</td>\n",
       "      <td>2.495626</td>\n",
       "      <td>415.391458</td>\n",
       "      <td>186.913270</td>\n",
       "      <td>371.282495</td>\n",
       "      <td>411.768150</td>\n",
       "      <td>422.965307</td>\n",
       "      <td>423.259102</td>\n",
       "      <td>55.806230</td>\n",
       "      <td>35.423900</td>\n",
       "      <td>1186.417700</td>\n",
       "      <td>26.293875</td>\n",
       "      <td>0.520470</td>\n",
       "      <td>0.450679</td>\n",
       "      <td>0.464507</td>\n",
       "      <td>0.504073</td>\n",
       "      <td>0.469449</td>\n",
       "      <td>0.453942</td>\n",
       "      <td>0.433258</td>\n",
       "      <td>0.431468</td>\n",
       "      <td>0.492326</td>\n",
       "      <td>42.169189</td>\n",
       "      <td>38.995439</td>\n",
       "      <td>424.697885</td>\n",
       "      <td>0.289957</td>\n",
       "      <td>24.325651</td>\n",
       "      <td>5.575779</td>\n",
       "      <td>7.480456e+05</td>\n",
       "      <td>1077252.70</td>\n",
       "      <td>-9.200040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>167</td>\n",
       "      <td>2018/7/23 8:00:00</td>\n",
       "      <td>0.61</td>\n",
       "      <td>254.428571</td>\n",
       "      <td>89.6</td>\n",
       "      <td>54.80</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.10</td>\n",
       "      <td>45.820</td>\n",
       "      <td>738.70</td>\n",
       "      <td>3.2</td>\n",
       "      <td>88.99</td>\n",
       "      <td>3.45</td>\n",
       "      <td>7.44</td>\n",
       "      <td>1.35</td>\n",
       "      <td>6.25</td>\n",
       "      <td>0.248665</td>\n",
       "      <td>17.721166</td>\n",
       "      <td>2.497041</td>\n",
       "      <td>699.109595</td>\n",
       "      <td>422.312170</td>\n",
       "      <td>419.326405</td>\n",
       "      <td>2.398573</td>\n",
       "      <td>61.651206</td>\n",
       "      <td>304.170097</td>\n",
       "      <td>2.408864</td>\n",
       "      <td>4.777457</td>\n",
       "      <td>0.659932</td>\n",
       "      <td>130.969347</td>\n",
       "      <td>54.993771</td>\n",
       "      <td>558.620155</td>\n",
       "      <td>39.659723</td>\n",
       "      <td>36.630371</td>\n",
       "      <td>974.489215</td>\n",
       "      <td>34.610186</td>\n",
       "      <td>525.719345</td>\n",
       "      <td>558.620155</td>\n",
       "      <td>0.995034</td>\n",
       "      <td>182.992077</td>\n",
       "      <td>437.787003</td>\n",
       "      <td>1006.066970</td>\n",
       "      <td>360.239993</td>\n",
       "      <td>798.044813</td>\n",
       "      <td>0.579989</td>\n",
       "      <td>0.502228</td>\n",
       "      <td>26.376381</td>\n",
       "      <td>139.540353</td>\n",
       "      <td>6254.115750</td>\n",
       "      <td>67.862938</td>\n",
       "      <td>0.123565</td>\n",
       "      <td>358.858695</td>\n",
       "      <td>1.989020</td>\n",
       "      <td>452.125270</td>\n",
       "      <td>-0.181439</td>\n",
       "      <td>0.053643</td>\n",
       "      <td>0.379523</td>\n",
       "      <td>2.998912</td>\n",
       "      <td>2.332971</td>\n",
       "      <td>136.922780</td>\n",
       "      <td>36.723528</td>\n",
       "      <td>2.300237</td>\n",
       "      <td>298.561710</td>\n",
       "      <td>79.664446</td>\n",
       "      <td>39.835600</td>\n",
       "      <td>297.837810</td>\n",
       "      <td>499.506202</td>\n",
       "      <td>47.266347</td>\n",
       "      <td>1.502574</td>\n",
       "      <td>6.944146e+05</td>\n",
       "      <td>1.712167e+05</td>\n",
       "      <td>1.369230e+06</td>\n",
       "      <td>648.956900</td>\n",
       "      <td>445.038902</td>\n",
       "      <td>8.079196e+05</td>\n",
       "      <td>6.014150e+05</td>\n",
       "      <td>924.110408</td>\n",
       "      <td>1325.572125</td>\n",
       "      <td>2.125517e+05</td>\n",
       "      <td>9.527724e+05</td>\n",
       "      <td>7.845864e+05</td>\n",
       "      <td>1.759745e+05</td>\n",
       "      <td>1668550.050</td>\n",
       "      <td>1.661761e+05</td>\n",
       "      <td>139.183763</td>\n",
       "      <td>2.680762</td>\n",
       "      <td>2.557168</td>\n",
       "      <td>164.952535</td>\n",
       "      <td>81.414414</td>\n",
       "      <td>34.135172</td>\n",
       "      <td>36.194765</td>\n",
       "      <td>0.379488</td>\n",
       "      <td>38.978827</td>\n",
       "      <td>-0.499568</td>\n",
       "      <td>-1.267368</td>\n",
       "      <td>0.401398</td>\n",
       "      <td>30.175725</td>\n",
       "      <td>268.531531</td>\n",
       "      <td>22.001770</td>\n",
       "      <td>30.842984</td>\n",
       "      <td>-1.289781</td>\n",
       "      <td>56.126652</td>\n",
       "      <td>38.813595</td>\n",
       "      <td>273.669420</td>\n",
       "      <td>38.006141</td>\n",
       "      <td>32.564025</td>\n",
       "      <td>31.232880</td>\n",
       "      <td>185.220227</td>\n",
       "      <td>0.155996</td>\n",
       "      <td>0.170302</td>\n",
       "      <td>4.807026</td>\n",
       "      <td>269.726333</td>\n",
       "      <td>299.188030</td>\n",
       "      <td>130.887978</td>\n",
       "      <td>66.087910</td>\n",
       "      <td>139.553927</td>\n",
       "      <td>72.363596</td>\n",
       "      <td>45.565941</td>\n",
       "      <td>49.182246</td>\n",
       "      <td>499.000927</td>\n",
       "      <td>496.716270</td>\n",
       "      <td>496.404910</td>\n",
       "      <td>47.946788</td>\n",
       "      <td>29.107637</td>\n",
       "      <td>0.991346</td>\n",
       "      <td>23.004720</td>\n",
       "      <td>757.082327</td>\n",
       "      <td>376.163045</td>\n",
       "      <td>2.992761</td>\n",
       "      <td>13951.583800</td>\n",
       "      <td>0.090721</td>\n",
       "      <td>-0.761226</td>\n",
       "      <td>302.394688</td>\n",
       "      <td>-1136.090825</td>\n",
       "      <td>275.667725</td>\n",
       "      <td>0.562474</td>\n",
       "      <td>2.964252</td>\n",
       "      <td>3.939155</td>\n",
       "      <td>-0.074627</td>\n",
       "      <td>3.273313</td>\n",
       "      <td>34.234586</td>\n",
       "      <td>54.356749</td>\n",
       "      <td>0.148742</td>\n",
       "      <td>6.520745</td>\n",
       "      <td>47.878225</td>\n",
       "      <td>445.978755</td>\n",
       "      <td>494.491595</td>\n",
       "      <td>422.713335</td>\n",
       "      <td>22.009293</td>\n",
       "      <td>419.631345</td>\n",
       "      <td>418.627090</td>\n",
       "      <td>417.115433</td>\n",
       "      <td>9.721973</td>\n",
       "      <td>1.659179</td>\n",
       "      <td>-0.121192</td>\n",
       "      <td>14.540091</td>\n",
       "      <td>2.273573</td>\n",
       "      <td>3.047405</td>\n",
       "      <td>6.944564</td>\n",
       "      <td>549.017040</td>\n",
       "      <td>4.782526</td>\n",
       "      <td>29.868130</td>\n",
       "      <td>29.572823</td>\n",
       "      <td>0.111675</td>\n",
       "      <td>29.660465</td>\n",
       "      <td>0.111580</td>\n",
       "      <td>29.598133</td>\n",
       "      <td>56.450738</td>\n",
       "      <td>56.556588</td>\n",
       "      <td>3.013086</td>\n",
       "      <td>2.286089</td>\n",
       "      <td>0.167054</td>\n",
       "      <td>446.307435</td>\n",
       "      <td>-0.168473</td>\n",
       "      <td>-0.067553</td>\n",
       "      <td>2.491996</td>\n",
       "      <td>412.212855</td>\n",
       "      <td>188.241373</td>\n",
       "      <td>372.693225</td>\n",
       "      <td>412.921870</td>\n",
       "      <td>418.532793</td>\n",
       "      <td>418.836008</td>\n",
       "      <td>65.673151</td>\n",
       "      <td>37.013230</td>\n",
       "      <td>1698.779600</td>\n",
       "      <td>30.097203</td>\n",
       "      <td>0.571100</td>\n",
       "      <td>0.453942</td>\n",
       "      <td>0.470241</td>\n",
       "      <td>0.501440</td>\n",
       "      <td>0.496211</td>\n",
       "      <td>0.475823</td>\n",
       "      <td>0.432396</td>\n",
       "      <td>0.460711</td>\n",
       "      <td>0.493490</td>\n",
       "      <td>28.385630</td>\n",
       "      <td>38.984290</td>\n",
       "      <td>422.535768</td>\n",
       "      <td>0.282758</td>\n",
       "      <td>22.987943</td>\n",
       "      <td>5.685402</td>\n",
       "      <td>2.032650e+06</td>\n",
       "      <td>2811629.05</td>\n",
       "      <td>-2.015496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>242</td>\n",
       "      <td>2017/10/25 8:00:00</td>\n",
       "      <td>0.70</td>\n",
       "      <td>296.714286</td>\n",
       "      <td>90.1</td>\n",
       "      <td>47.54</td>\n",
       "      <td>30.4</td>\n",
       "      <td>22.06</td>\n",
       "      <td>47.795</td>\n",
       "      <td>733.60</td>\n",
       "      <td>4.8</td>\n",
       "      <td>89.40</td>\n",
       "      <td>1.97</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1.30</td>\n",
       "      <td>3.71</td>\n",
       "      <td>0.251655</td>\n",
       "      <td>20.940268</td>\n",
       "      <td>2.563977</td>\n",
       "      <td>749.973385</td>\n",
       "      <td>424.563570</td>\n",
       "      <td>421.780680</td>\n",
       "      <td>2.463150</td>\n",
       "      <td>61.303989</td>\n",
       "      <td>308.704093</td>\n",
       "      <td>2.473481</td>\n",
       "      <td>5.796858</td>\n",
       "      <td>0.650195</td>\n",
       "      <td>130.141368</td>\n",
       "      <td>49.170634</td>\n",
       "      <td>652.637630</td>\n",
       "      <td>29.769675</td>\n",
       "      <td>33.081298</td>\n",
       "      <td>756.719975</td>\n",
       "      <td>24.469261</td>\n",
       "      <td>445.088357</td>\n",
       "      <td>652.637630</td>\n",
       "      <td>0.991136</td>\n",
       "      <td>197.816320</td>\n",
       "      <td>460.616330</td>\n",
       "      <td>55.394783</td>\n",
       "      <td>340.893040</td>\n",
       "      <td>473.587110</td>\n",
       "      <td>0.622823</td>\n",
       "      <td>0.484988</td>\n",
       "      <td>0.375255</td>\n",
       "      <td>138.177163</td>\n",
       "      <td>6404.956850</td>\n",
       "      <td>65.132904</td>\n",
       "      <td>0.115431</td>\n",
       "      <td>366.359255</td>\n",
       "      <td>2.228608</td>\n",
       "      <td>427.046805</td>\n",
       "      <td>-0.371663</td>\n",
       "      <td>0.147711</td>\n",
       "      <td>0.369888</td>\n",
       "      <td>3.199465</td>\n",
       "      <td>2.399146</td>\n",
       "      <td>133.753778</td>\n",
       "      <td>29.742057</td>\n",
       "      <td>2.366716</td>\n",
       "      <td>280.946658</td>\n",
       "      <td>80.954334</td>\n",
       "      <td>37.509870</td>\n",
       "      <td>281.039465</td>\n",
       "      <td>493.262185</td>\n",
       "      <td>45.170214</td>\n",
       "      <td>1.550030</td>\n",
       "      <td>1.179205e+07</td>\n",
       "      <td>3.401917e+06</td>\n",
       "      <td>2.246727e+07</td>\n",
       "      <td>87977.017750</td>\n",
       "      <td>18846.127000</td>\n",
       "      <td>2.296608e+07</td>\n",
       "      <td>1.227189e+07</td>\n",
       "      <td>68626.862250</td>\n",
       "      <td>107539.865000</td>\n",
       "      <td>3.085414e+06</td>\n",
       "      <td>5.014305e+07</td>\n",
       "      <td>2.609038e+07</td>\n",
       "      <td>3.303988e+06</td>\n",
       "      <td>5615561.950</td>\n",
       "      <td>3.204380e+06</td>\n",
       "      <td>136.502563</td>\n",
       "      <td>2.774492</td>\n",
       "      <td>2.659061</td>\n",
       "      <td>155.505442</td>\n",
       "      <td>40.998764</td>\n",
       "      <td>24.185749</td>\n",
       "      <td>30.561211</td>\n",
       "      <td>0.370930</td>\n",
       "      <td>44.909727</td>\n",
       "      <td>0.150926</td>\n",
       "      <td>-1.279213</td>\n",
       "      <td>0.476641</td>\n",
       "      <td>20.610205</td>\n",
       "      <td>303.825845</td>\n",
       "      <td>22.412961</td>\n",
       "      <td>19.848352</td>\n",
       "      <td>-1.355684</td>\n",
       "      <td>37.632719</td>\n",
       "      <td>34.758738</td>\n",
       "      <td>276.865218</td>\n",
       "      <td>16.447419</td>\n",
       "      <td>31.642423</td>\n",
       "      <td>23.493750</td>\n",
       "      <td>215.060210</td>\n",
       "      <td>0.133003</td>\n",
       "      <td>0.149726</td>\n",
       "      <td>5.922259</td>\n",
       "      <td>292.791792</td>\n",
       "      <td>270.215040</td>\n",
       "      <td>128.180030</td>\n",
       "      <td>68.677514</td>\n",
       "      <td>138.527610</td>\n",
       "      <td>75.985862</td>\n",
       "      <td>45.248008</td>\n",
       "      <td>45.378143</td>\n",
       "      <td>135.090120</td>\n",
       "      <td>489.862242</td>\n",
       "      <td>491.335970</td>\n",
       "      <td>44.516599</td>\n",
       "      <td>25.115561</td>\n",
       "      <td>1.168427</td>\n",
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       "      <td>718.831395</td>\n",
       "      <td>346.406957</td>\n",
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       "      <td>8253.802100</td>\n",
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       "      <td>277.698655</td>\n",
       "      <td>-1255.125200</td>\n",
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       "      <td>0.592460</td>\n",
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       "      <td>60.746384</td>\n",
       "      <td>23.516881</td>\n",
       "      <td>0.149353</td>\n",
       "      <td>5.685354</td>\n",
       "      <td>98.616242</td>\n",
       "      <td>441.824235</td>\n",
       "      <td>489.396590</td>\n",
       "      <td>426.080402</td>\n",
       "      <td>33.523419</td>\n",
       "      <td>421.815420</td>\n",
       "      <td>420.969530</td>\n",
       "      <td>418.501955</td>\n",
       "      <td>8.802798</td>\n",
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       "      <td>-0.378456</td>\n",
       "      <td>11.761831</td>\n",
       "      <td>5.211471</td>\n",
       "      <td>35.916541</td>\n",
       "      <td>37.113658</td>\n",
       "      <td>529.042520</td>\n",
       "      <td>5.804188</td>\n",
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       "      <td>17.721639</td>\n",
       "      <td>0.064873</td>\n",
       "      <td>18.880591</td>\n",
       "      <td>0.065452</td>\n",
       "      <td>18.009532</td>\n",
       "      <td>21.404255</td>\n",
       "      <td>20.884158</td>\n",
       "      <td>0.140376</td>\n",
       "      <td>0.099229</td>\n",
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       "      <td>341.348000</td>\n",
       "      <td>386.741845</td>\n",
       "      <td>342.604172</td>\n",
       "      <td>343.682000</td>\n",
       "      <td>61.058466</td>\n",
       "      <td>28.717880</td>\n",
       "      <td>1639.313475</td>\n",
       "      <td>18.349903</td>\n",
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       "      <td>0.632997</td>\n",
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       "      <td>0.733043</td>\n",
       "      <td>0.682877</td>\n",
       "      <td>0.677623</td>\n",
       "      <td>0.647101</td>\n",
       "      <td>54.817995</td>\n",
       "      <td>44.956767</td>\n",
       "      <td>426.539975</td>\n",
       "      <td>0.281834</td>\n",
       "      <td>22.871400</td>\n",
       "      <td>5.841039</td>\n",
       "      <td>1.036639e+07</td>\n",
       "      <td>12505335.25</td>\n",
       "      <td>-71.551618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>194</td>\n",
       "      <td>2018/3/16 8:00:00</td>\n",
       "      <td>0.71</td>\n",
       "      <td>307.285714</td>\n",
       "      <td>90.2</td>\n",
       "      <td>53.60</td>\n",
       "      <td>25.9</td>\n",
       "      <td>20.50</td>\n",
       "      <td>58.110</td>\n",
       "      <td>721.80</td>\n",
       "      <td>3.2</td>\n",
       "      <td>89.49</td>\n",
       "      <td>9.37</td>\n",
       "      <td>12.19</td>\n",
       "      <td>2.47</td>\n",
       "      <td>8.84</td>\n",
       "      <td>0.263415</td>\n",
       "      <td>21.438785</td>\n",
       "      <td>2.498833</td>\n",
       "      <td>757.935920</td>\n",
       "      <td>428.609537</td>\n",
       "      <td>425.822545</td>\n",
       "      <td>2.381479</td>\n",
       "      <td>75.787407</td>\n",
       "      <td>255.761750</td>\n",
       "      <td>2.397072</td>\n",
       "      <td>5.763151</td>\n",
       "      <td>0.659987</td>\n",
       "      <td>125.809107</td>\n",
       "      <td>50.015678</td>\n",
       "      <td>643.764740</td>\n",
       "      <td>28.324245</td>\n",
       "      <td>31.850250</td>\n",
       "      <td>730.613335</td>\n",
       "      <td>17.155943</td>\n",
       "      <td>421.129715</td>\n",
       "      <td>643.764740</td>\n",
       "      <td>0.992234</td>\n",
       "      <td>208.955015</td>\n",
       "      <td>412.924465</td>\n",
       "      <td>1953.330162</td>\n",
       "      <td>386.236595</td>\n",
       "      <td>481.829558</td>\n",
       "      <td>0.645367</td>\n",
       "      <td>0.533411</td>\n",
       "      <td>34.333231</td>\n",
       "      <td>130.447293</td>\n",
       "      <td>6299.934525</td>\n",
       "      <td>62.128851</td>\n",
       "      <td>0.129386</td>\n",
       "      <td>366.913362</td>\n",
       "      <td>2.204112</td>\n",
       "      <td>413.107987</td>\n",
       "      <td>-0.430940</td>\n",
       "      <td>0.134467</td>\n",
       "      <td>0.369890</td>\n",
       "      <td>3.218341</td>\n",
       "      <td>2.315751</td>\n",
       "      <td>133.386507</td>\n",
       "      <td>34.332877</td>\n",
       "      <td>2.280710</td>\n",
       "      <td>286.655380</td>\n",
       "      <td>70.191027</td>\n",
       "      <td>38.228586</td>\n",
       "      <td>319.468318</td>\n",
       "      <td>502.469375</td>\n",
       "      <td>34.531439</td>\n",
       "      <td>1.617814</td>\n",
       "      <td>1.338561e+07</td>\n",
       "      <td>3.881127e+06</td>\n",
       "      <td>2.541804e+07</td>\n",
       "      <td>111421.405000</td>\n",
       "      <td>20104.390000</td>\n",
       "      <td>2.442505e+07</td>\n",
       "      <td>1.372383e+07</td>\n",
       "      <td>70779.162250</td>\n",
       "      <td>113679.410000</td>\n",
       "      <td>3.455172e+06</td>\n",
       "      <td>5.195231e+07</td>\n",
       "      <td>2.829605e+07</td>\n",
       "      <td>3.751264e+06</td>\n",
       "      <td>3547385.900</td>\n",
       "      <td>3.648529e+06</td>\n",
       "      <td>135.924235</td>\n",
       "      <td>2.707743</td>\n",
       "      <td>2.578378</td>\n",
       "      <td>160.902925</td>\n",
       "      <td>47.098937</td>\n",
       "      <td>16.954750</td>\n",
       "      <td>35.770239</td>\n",
       "      <td>0.370831</td>\n",
       "      <td>44.894316</td>\n",
       "      <td>0.468730</td>\n",
       "      <td>-1.408170</td>\n",
       "      <td>0.450370</td>\n",
       "      <td>12.553831</td>\n",
       "      <td>303.162272</td>\n",
       "      <td>22.727590</td>\n",
       "      <td>12.274428</td>\n",
       "      <td>-1.420090</td>\n",
       "      <td>56.575285</td>\n",
       "      <td>19.998121</td>\n",
       "      <td>279.091670</td>\n",
       "      <td>48.348648</td>\n",
       "      <td>18.454996</td>\n",
       "      <td>15.909398</td>\n",
       "      <td>181.960695</td>\n",
       "      <td>0.164867</td>\n",
       "      <td>0.168215</td>\n",
       "      <td>5.033674</td>\n",
       "      <td>235.391855</td>\n",
       "      <td>279.748173</td>\n",
       "      <td>127.582747</td>\n",
       "      <td>60.510428</td>\n",
       "      <td>133.781410</td>\n",
       "      <td>68.908481</td>\n",
       "      <td>39.167082</td>\n",
       "      <td>48.981927</td>\n",
       "      <td>244.805149</td>\n",
       "      <td>498.836230</td>\n",
       "      <td>498.646727</td>\n",
       "      <td>34.354497</td>\n",
       "      <td>31.560384</td>\n",
       "      <td>1.255594</td>\n",
       "      <td>28.279919</td>\n",
       "      <td>692.664610</td>\n",
       "      <td>328.453760</td>\n",
       "      <td>3.214484</td>\n",
       "      <td>7338.619725</td>\n",
       "      <td>0.043797</td>\n",
       "      <td>-1.014976</td>\n",
       "      <td>254.771845</td>\n",
       "      <td>-1361.032275</td>\n",
       "      <td>227.394763</td>\n",
       "      <td>0.617396</td>\n",
       "      <td>0.979879</td>\n",
       "      <td>-4.021735</td>\n",
       "      <td>-0.040761</td>\n",
       "      <td>4.149546</td>\n",
       "      <td>50.657814</td>\n",
       "      <td>18.907073</td>\n",
       "      <td>0.149323</td>\n",
       "      <td>9.906170</td>\n",
       "      <td>82.905232</td>\n",
       "      <td>459.586900</td>\n",
       "      <td>497.899375</td>\n",
       "      <td>429.774970</td>\n",
       "      <td>31.734696</td>\n",
       "      <td>426.264512</td>\n",
       "      <td>424.951447</td>\n",
       "      <td>422.871210</td>\n",
       "      <td>4.665347</td>\n",
       "      <td>9.847435</td>\n",
       "      <td>-0.375334</td>\n",
       "      <td>13.312953</td>\n",
       "      <td>2.609494</td>\n",
       "      <td>42.312529</td>\n",
       "      <td>43.819674</td>\n",
       "      <td>537.495522</td>\n",
       "      <td>5.762571</td>\n",
       "      <td>9.973539</td>\n",
       "      <td>8.201709</td>\n",
       "      <td>0.031015</td>\n",
       "      <td>10.124758</td>\n",
       "      <td>0.033004</td>\n",
       "      <td>8.419809</td>\n",
       "      <td>10.897261</td>\n",
       "      <td>10.045660</td>\n",
       "      <td>0.015648</td>\n",
       "      <td>0.003383</td>\n",
       "      <td>0.165508</td>\n",
       "      <td>357.026378</td>\n",
       "      <td>-0.404606</td>\n",
       "      <td>-0.297383</td>\n",
       "      <td>2.496320</td>\n",
       "      <td>411.150967</td>\n",
       "      <td>323.671690</td>\n",
       "      <td>275.942325</td>\n",
       "      <td>316.015278</td>\n",
       "      <td>351.280415</td>\n",
       "      <td>352.213132</td>\n",
       "      <td>53.049863</td>\n",
       "      <td>17.984170</td>\n",
       "      <td>1284.308275</td>\n",
       "      <td>10.072203</td>\n",
       "      <td>0.545910</td>\n",
       "      <td>0.096724</td>\n",
       "      <td>0.597686</td>\n",
       "      <td>0.466199</td>\n",
       "      <td>0.560424</td>\n",
       "      <td>0.728496</td>\n",
       "      <td>0.692422</td>\n",
       "      <td>0.658572</td>\n",
       "      <td>0.693177</td>\n",
       "      <td>40.053319</td>\n",
       "      <td>44.895846</td>\n",
       "      <td>429.980535</td>\n",
       "      <td>0.279306</td>\n",
       "      <td>28.266832</td>\n",
       "      <td>4.446526</td>\n",
       "      <td>1.714475e+07</td>\n",
       "      <td>20987765.50</td>\n",
       "      <td>-35.115716</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     样本编号                  时间  RON损失    原料性质：硫含量  原料性质：辛烷值  原料性质：饱和烃  原料性质：烯烃  \\\n",
       "111   142   2019/1/18 8:00:00   0.20  153.428571      85.3     58.50     17.6   \n",
       "239   179   2018/6/25 8:00:00   0.54  231.428571      90.1     50.40     23.4   \n",
       "131   167   2018/7/23 8:00:00   0.61  254.428571      89.6     54.80     22.1   \n",
       "261   242  2017/10/25 8:00:00   0.70  296.714286      90.1     47.54     30.4   \n",
       "149   194   2018/3/16 8:00:00   0.71  307.285714      90.2     53.60     25.9   \n",
       "\n",
       "     原料性质：芳烃  原料性质：溴值  原料性质：密度  产品性质：硫含量  产品性质：辛烷值  待生吸附剂性质：焦炭  待生吸附剂性质：S  \\\n",
       "111    23.90   45.150   720.80       3.2     85.10        2.45       8.85   \n",
       "239    26.20   43.820   735.15       4.3     89.56        3.48      10.67   \n",
       "131    23.10   45.820   738.70       3.2     88.99        3.45       7.44   \n",
       "261    22.06   47.795   733.60       4.8     89.40        1.97       4.70   \n",
       "149    20.50   58.110   721.80       3.2     89.49        9.37      12.19   \n",
       "\n",
       "     再生吸附剂性质：焦炭  再生吸附剂性质：S  S-ZORB.CAL_H2.PV  S-ZORB.PDI_2102.PV  \\\n",
       "111        1.27       6.69          0.302291           23.189189   \n",
       "239        0.90       6.35          0.232117           17.440714   \n",
       "131        1.35       6.25          0.248665           17.721166   \n",
       "261        1.30       3.71          0.251655           20.940268   \n",
       "149        2.47       8.84          0.263415           21.438785   \n",
       "\n",
       "     S-ZORB.PT_2801.PV  S-ZORB.FC_2801.PV  S-ZORB.TE_2103.PV  \\\n",
       "111           2.467430         652.255985         421.857275   \n",
       "239           2.504474         651.170082         423.964413   \n",
       "131           2.497041         699.109595         422.312170   \n",
       "261           2.563977         749.973385         424.563570   \n",
       "149           2.498833         757.935920         428.609537   \n",
       "\n",
       "     S-ZORB.TE_2005.PV  S-ZORB.PT_2101.PV  S-ZORB.PDT_2104.PV  \\\n",
       "111         415.880212           2.354010           81.158234   \n",
       "239         420.478555           2.401949           65.193053   \n",
       "131         419.326405           2.398573           61.651206   \n",
       "261         421.780680           2.463150           61.303989   \n",
       "149         425.822545           2.381479           75.787407   \n",
       "\n",
       "     S-ZORB.TE_2301.PV  S-ZORB.PT_2301.PV  S-ZORB.PC_2105.PV  \\\n",
       "111         374.109665           2.366296           4.795737   \n",
       "239         306.001070           2.414110           4.798732   \n",
       "131         304.170097           2.408864           4.777457   \n",
       "261         308.704093           2.473481           5.796858   \n",
       "149         255.761750           2.397072           5.763151   \n",
       "\n",
       "     S-ZORB.PC_5101.PV  S-ZORB.TC_5005.PV  S-ZORB.LC_5001.PV  \\\n",
       "111           0.660073         118.851450          55.040801   \n",
       "239           0.660179         128.249900          46.019762   \n",
       "131           0.659932         130.969347          54.993771   \n",
       "261           0.650195         130.141368          49.170634   \n",
       "149           0.659987         125.809107          50.015678   \n",
       "\n",
       "     S-ZORB.LC_5101.PV  S-ZORB.TE_5102.PV  S-ZORB.TE_5202.PV  \\\n",
       "111          49.987329          25.588707          34.683582   \n",
       "239         556.221002          33.124049          36.897491   \n",
       "131         558.620155          39.659723          36.630371   \n",
       "261         652.637630          29.769675          33.081298   \n",
       "149         643.764740          28.324245          31.850250   \n",
       "\n",
       "     S-ZORB.FT_5101.PV  S-ZORB.TE_9001.PV  S-ZORB.FT_9001.PV  \\\n",
       "111         737.834190          17.345706         466.062710   \n",
       "239        1254.662175          29.282571         540.493378   \n",
       "131         974.489215          34.610186         525.719345   \n",
       "261         756.719975          24.469261         445.088357   \n",
       "149         730.613335          17.155943         421.129715   \n",
       "\n",
       "     S-ZORB.FT_9403.PV  S-ZORB.PT_9403.PV  S-ZORB.TE_9301.PV  \\\n",
       "111         567.702378           0.992984         205.330502   \n",
       "239         556.221002           0.994322         206.939877   \n",
       "131         558.620155           0.995034         182.992077   \n",
       "261         652.637630           0.991136         197.816320   \n",
       "149         643.764740           0.992234         208.955015   \n",
       "\n",
       "     S-ZORB.FT_9202.PV  S-ZORB.FT_9302.PV  S-ZORB.FT_3301.PV  \\\n",
       "111         425.288772        4603.358500         251.303697   \n",
       "239         441.412810        1034.989777         368.400145   \n",
       "131         437.787003        1006.066970         360.239993   \n",
       "261         460.616330          55.394783         340.893040   \n",
       "149         412.924465        1953.330162         386.236595   \n",
       "\n",
       "     S-ZORB.FT_9402.PV  S-ZORB.PT_9402.PV  S-ZORB.PT_9401.PV  \\\n",
       "111         358.665613           0.629209           0.547578   \n",
       "239         740.214717           0.615811           0.514686   \n",
       "131         798.044813           0.579989           0.502228   \n",
       "261         473.587110           0.622823           0.484988   \n",
       "149         481.829558           0.645367           0.533411   \n",
       "\n",
       "     S-ZORB.PDC_2502.PV  S-ZORB.FC_1005.PV  S-ZORB.FC_1102.PV  \\\n",
       "111           19.074767         140.109633        8665.056575   \n",
       "239           27.185475         144.708300        6082.223150   \n",
       "131           26.376381         139.540353        6254.115750   \n",
       "261            0.375255         138.177163        6404.956850   \n",
       "149           34.333231         130.447293        6299.934525   \n",
       "\n",
       "     S-ZORB.TE_1105.PV  S-ZORB.PDI_1102.PV  S-ZORB.TE_1601.PV  \\\n",
       "111          47.826013            0.162193         363.093860   \n",
       "239          68.908238            0.125474         362.785255   \n",
       "131          67.862938            0.123565         358.858695   \n",
       "261          65.132904            0.115431         366.359255   \n",
       "149          62.128851            0.129386         366.913362   \n",
       "\n",
       "     S-ZORB.AC_6001.PV  S-ZORB.TE_1608.PV  S-ZORB.PT_6002.PV  \\\n",
       "111           2.003106         440.924715          -0.246122   \n",
       "239           2.298722         455.054298          -0.190461   \n",
       "131           1.989020         452.125270          -0.181439   \n",
       "261           2.228608         427.046805          -0.371663   \n",
       "149           2.204112         413.107987          -0.430940   \n",
       "\n",
       "     S-ZORB.PC_1603.PV  S-ZORB.PT_1602A.PV  S-ZORB.PC_1301.PV  \\\n",
       "111           0.051094            0.382390           3.054283   \n",
       "239           0.049344            0.380161           3.001516   \n",
       "131           0.053643            0.379523           2.998912   \n",
       "261           0.147711            0.369888           3.199465   \n",
       "149           0.134467            0.369890           3.218341   \n",
       "\n",
       "     S-ZORB.PT_1201.PV  S-ZORB.TE_1201.PV  S-ZORB.TE_1203.PV  \\\n",
       "111           2.271794         113.701678          28.601333   \n",
       "239           2.331590         139.093382          34.648286   \n",
       "131           2.332971         136.922780          36.723528   \n",
       "261           2.399146         133.753778          29.742057   \n",
       "149           2.315751         133.386507          34.332877   \n",
       "\n",
       "     S-ZORB.PC_1202.PV  S-ZORB.TC_2801.PV  S-ZORB.FC_2601.PV  \\\n",
       "111           2.251315         269.784730          74.025252   \n",
       "239           2.299057         298.292110          80.214898   \n",
       "131           2.300237         298.561710          79.664446   \n",
       "261           2.366716         280.946658          80.954334   \n",
       "149           2.280710         286.655380          70.191027   \n",
       "\n",
       "     S-ZORB.PDT_2604.PV  S-ZORB.TE_2601.PV  S-ZORB.TC_2607.PV  \\\n",
       "111           37.942943         270.117948         505.343350   \n",
       "239           42.621959         282.123227         487.105630   \n",
       "131           39.835600         297.837810         499.506202   \n",
       "261           37.509870         281.039465         493.262185   \n",
       "149           38.228586         319.468318         502.469375   \n",
       "\n",
       "     S-ZORB.PDI_2703A.PV  S-ZORB.PT_1501.PV  S-ZORB.FT_9001.TOTAL  \\\n",
       "111            33.569865           1.968169          2.860659e+06   \n",
       "239            32.826797           1.544113          3.517421e+05   \n",
       "131            47.266347           1.502574          6.944146e+05   \n",
       "261            45.170214           1.550030          1.179205e+07   \n",
       "149            34.531439           1.617814          1.338561e+07   \n",
       "\n",
       "     S-ZORB.FT_5201.TOTAL  S-ZORB.FT_5101.TOTAL  S-ZORB.FT_9101.TOTAL  \\\n",
       "111          7.071382e+05          5.852788e+06           1394.796000   \n",
       "239          8.551135e+04          7.416220e+05            486.466615   \n",
       "131          1.712167e+05          1.369230e+06            648.956900   \n",
       "261          3.401917e+06          2.246727e+07          87977.017750   \n",
       "149          3.881127e+06          2.541804e+07         111421.405000   \n",
       "\n",
       "     S-ZORB.FT_3301.TOTAL  S-ZORB.FT_9201.TOTAL  S-ZORB.FT_9202.TOTAL  \\\n",
       "111           1689.491550          2.660594e+06          2.415157e+06   \n",
       "239            219.030810          5.113878e+05          3.110871e+05   \n",
       "131            445.038902          8.079196e+05          6.014150e+05   \n",
       "261          18846.127000          2.296608e+07          1.227189e+07   \n",
       "149          20104.390000          2.442505e+07          1.372383e+07   \n",
       "\n",
       "     S-ZORB.FT_9301.TOTAL  S-ZORB.FT_9302.TOTAL  S-ZORB.FT_9401.TOTAL  \\\n",
       "111           6143.337925          18733.112000          6.879282e+05   \n",
       "239            586.456920            660.774940          1.392635e+05   \n",
       "131            924.110408           1325.572125          2.125517e+05   \n",
       "261          68626.862250         107539.865000          3.085414e+06   \n",
       "149          70779.162250         113679.410000          3.455172e+06   \n",
       "\n",
       "     S-ZORB.FT_9402.TOTAL  S-ZORB.FT_9403.TOTAL  S-ZORB.FC_1101.TOTAL  \\\n",
       "111          3.082328e+06          3.151981e+06          7.303289e+05   \n",
       "239          4.536035e+05          4.133201e+05          8.822381e+04   \n",
       "131          9.527724e+05          7.845864e+05          1.759745e+05   \n",
       "261          5.014305e+07          2.609038e+07          3.303988e+06   \n",
       "149          5.195231e+07          2.829605e+07          3.751264e+06   \n",
       "\n",
       "     S-ZORB.FT_1204.TOTAL  S-ZORB.FT_1001.TOTAL  S-ZORB.TE_1101.DACA  \\\n",
       "111            174935.690          6.718409e+05           115.515807   \n",
       "239           2076359.375          8.420167e+04           141.161082   \n",
       "131           1668550.050          1.661761e+05           139.183763   \n",
       "261           5615561.950          3.204380e+06           136.502563   \n",
       "149           3547385.900          3.648529e+06           135.924235   \n",
       "\n",
       "     S-ZORB.PT_1102.DACA  S-ZORB.PT_1103.DACA  S-ZORB.TE_1106.DACA  \\\n",
       "111             2.678865             2.516416           122.803100   \n",
       "239             2.703914             2.578487           164.783845   \n",
       "131             2.680762             2.557168           164.952535   \n",
       "261             2.774492             2.659061           155.505442   \n",
       "149             2.707743             2.578378           160.902925   \n",
       "\n",
       "     S-ZORB.LI_9102.DACA  S-ZORB.TE_9003.DACA  S-ZORB.TE_9002.DACA  \\\n",
       "111            54.138311            17.709174            33.382268   \n",
       "239            87.324372            29.001526            31.734695   \n",
       "131            81.414414            34.135172            36.194765   \n",
       "261            40.998764            24.185749            30.561211   \n",
       "149            47.098937            16.954750            35.770239   \n",
       "\n",
       "     S-ZORB.PC_9002.DACA  S-ZORB.LC_5102.DACA  S-ZORB.LT_3801.DACA  \\\n",
       "111             0.383522            40.019718             0.718196   \n",
       "239             0.380075            38.993849            -0.171501   \n",
       "131             0.379488            38.978827            -0.499568   \n",
       "261             0.370930            44.909727             0.150926   \n",
       "149             0.370831            44.894316             0.468730   \n",
       "\n",
       "     S-ZORB.LT_3101.DACA  S-ZORB.PC_3101.DACA  S-ZORB.TE_3101.DACA  \\\n",
       "111            -1.278075             0.399145             7.677337   \n",
       "239            -1.266395             0.399001            26.482363   \n",
       "131            -1.267368             0.401398            30.175725   \n",
       "261            -1.279213             0.476641            20.610205   \n",
       "149            -1.408170             0.450370            12.553831   \n",
       "\n",
       "     S-ZORB.FT_3303.DACA  S-ZORB.TE_1501.DACA  S-ZORB.TE_1502.DACA  \\\n",
       "111           170.176559            21.954300             9.111824   \n",
       "239           290.059087            22.419811            27.093236   \n",
       "131           268.531531            22.001770            30.842984   \n",
       "261           303.825845            22.412961            19.848352   \n",
       "149           303.162272            22.727590            12.274428   \n",
       "\n",
       "     S-ZORB.LT_2101.DACA  S-ZORB.FT_2701.DACA  S-ZORB.FC_2702.DACA  \\\n",
       "111            -1.340856            15.306804            41.307959   \n",
       "239            -1.290769            58.026285            29.014827   \n",
       "131            -1.289781            56.126652            38.813595   \n",
       "261            -1.355684            37.632719            34.758738   \n",
       "149            -1.420090            56.575285            19.998121   \n",
       "\n",
       "     S-ZORB.TC_2702.DACA  S-ZORB.LT_2901.DACA  S-ZORB.TE_2901.DACA  \\\n",
       "111           260.493843            30.705983            13.933394   \n",
       "239           260.082595            22.860594            30.915094   \n",
       "131           273.669420            38.006141            32.564025   \n",
       "261           276.865218            16.447419            31.642423   \n",
       "149           279.091670            48.348648            18.454996   \n",
       "\n",
       "     S-ZORB.TE_2902.DACA  S-ZORB.TE_2501.DACA  S-ZORB.PT_2501.DACA  \\\n",
       "111            15.015881           232.452760             0.145637   \n",
       "239            32.578755           211.554955             0.155537   \n",
       "131            31.232880           185.220227             0.155996   \n",
       "261            23.493750           215.060210             0.133003   \n",
       "149            15.909398           181.960695             0.164867   \n",
       "\n",
       "     S-ZORB.PT_2502.DACA  S-ZORB.FT_2433.DACA  S-ZORB.TE_2401.DACA  \\\n",
       "111             0.160647             5.402442           323.749950   \n",
       "239             0.172283             4.737708           265.687587   \n",
       "131             0.170302             4.807026           269.726333   \n",
       "261             0.149726             5.922259           292.791792   \n",
       "149             0.168215             5.033674           235.391855   \n",
       "\n",
       "     S-ZORB.SIS_TE_2802  S-ZORB.TE_5002.DACA  S-ZORB.TE_5004.DACA  \\\n",
       "111          271.326315           110.942325            54.271912   \n",
       "239          299.148343           132.893435            51.695513   \n",
       "131          299.188030           130.887978            66.087910   \n",
       "261          270.215040           128.180030            68.677514   \n",
       "149          279.748173           127.582747            60.510428   \n",
       "\n",
       "     S-ZORB.TE_5006.DACA  S-ZORB.TE_5003.DACA  S-ZORB.TE_5201.DACA  \\\n",
       "111           131.747580            62.882536            64.592642   \n",
       "239           139.064222            55.503849            55.931638   \n",
       "131           139.553927            72.363596            45.565941   \n",
       "261           138.527610            75.985862            45.248008   \n",
       "149           133.781410            68.908481            39.167082   \n",
       "\n",
       "     S-ZORB.TE_5101.DACA  S-ZORB.FT_2431.DACA  S-ZORB.SIS_TE_2606.PV  \\\n",
       "111            44.430071           492.527505             502.677805   \n",
       "239            46.354386           269.510851             484.222753   \n",
       "131            49.182246           499.000927             496.716270   \n",
       "261            45.378143           135.090120             489.862242   \n",
       "149            48.981927           244.805149             498.836230   \n",
       "\n",
       "     S-ZORB.SIS_TE_2605.PV  S-ZORB.PDT_2704.DACA  S-ZORB.PDC_2702.DACA  \\\n",
       "111             501.299860             33.422755             24.616618   \n",
       "239             484.574435             33.122203             31.642861   \n",
       "131             496.404910             47.946788             29.107637   \n",
       "261             491.335970             44.516599             25.115561   \n",
       "149             498.646727             34.354497             31.560384   \n",
       "\n",
       "     S-ZORB.PT_6009.DACA  S-ZORB.LI_2104.DACA  S-ZORB.TE_6002.DACA  \\\n",
       "111             1.142250            30.279219           735.242415   \n",
       "239             1.025846            24.321275           757.227392   \n",
       "131             0.991346            23.004720           757.082327   \n",
       "261             1.168427            22.871825           718.831395   \n",
       "149             1.255594            28.279919           692.664610   \n",
       "\n",
       "     S-ZORB.TE_6001.DACA  S-ZORB.PT_1101.DACA  S-ZORB.FC_5103.DACA  \\\n",
       "111           375.336275             3.053792          9689.481200   \n",
       "239           381.810445             2.995656          7538.660150   \n",
       "131           376.163045             2.992761         13951.583800   \n",
       "261           346.406957             3.193825          8253.802100   \n",
       "149           328.453760             3.214484          7338.619725   \n",
       "\n",
       "     S-ZORB.PDT_3601.DACA  S-ZORB.PT_6006.DACA  S-ZORB.SIS_TE_6009.PV  \\\n",
       "111              0.089603            -0.762954             297.487037   \n",
       "239              0.101576            -0.771467             307.853712   \n",
       "131              0.090721            -0.761226             302.394688   \n",
       "261              0.000036            -0.940165             277.698655   \n",
       "149              0.043797            -1.014976             254.771845   \n",
       "\n",
       "     S-ZORB.SIS_PT_6007.PV  S-ZORB.TE_6008.DACA  S-ZORB.PT_5201.DACA  \\\n",
       "111           -1124.399725           267.230527             0.624863   \n",
       "239           -1154.638450           280.822052             0.570104   \n",
       "131           -1136.090825           275.667725             0.562474   \n",
       "261           -1255.125200           247.943500             0.592460   \n",
       "149           -1361.032275           227.394763             0.617396   \n",
       "\n",
       "     S-ZORB.PC_3501.DACA  S-ZORB.LT_9101.DACA  S-ZORB.PT_6003.DACA  \\\n",
       "111             3.012523             7.467458            -0.049358   \n",
       "239             2.959342             2.255373            -0.071439   \n",
       "131             2.964252             3.939155            -0.074627   \n",
       "261             0.250319            -4.017022            -0.047236   \n",
       "149             0.979879            -4.021735            -0.040761   \n",
       "\n",
       "     S-ZORB.PDI_2105.DACA  S-ZORB.BS_LT_2401.PV  S-ZORB.FT_3701.DACA  \\\n",
       "111              2.831036             29.827915            39.468163   \n",
       "239              3.254476             29.485272            34.618066   \n",
       "131              3.273313             34.234586            54.356749   \n",
       "261              4.251329             60.746384            23.516881   \n",
       "149              4.149546             50.657814            18.907073   \n",
       "\n",
       "     S-ZORB.PT_2603.DACA  S-ZORB.PDT_2606.DACA  S-ZORB.ZT_2634.DACA  \\\n",
       "111             0.146417             11.204336            42.411540   \n",
       "239             0.151099             10.017687            52.215769   \n",
       "131             0.148742              6.520745            47.878225   \n",
       "261             0.149353              5.685354            98.616242   \n",
       "149             0.149323              9.906170            82.905232   \n",
       "\n",
       "     S-ZORB.TE_2603.DACA  S-ZORB.TE_2604.DACA  S-ZORB.TE_2104.DACA  \\\n",
       "111           424.709835           500.387162           423.928120   \n",
       "239           446.566818           482.373215           424.751535   \n",
       "131           445.978755           494.491595           422.713335   \n",
       "261           441.824235           489.396590           426.080402   \n",
       "149           459.586900           497.899375           429.774970   \n",
       "\n",
       "     S-ZORB.PDT_2001.DACA  S-ZORB.TE_2002.DACA  S-ZORB.TE_2004.DACA  \\\n",
       "111             27.303293           417.029705           415.446300   \n",
       "239             24.347757           420.892835           419.781605   \n",
       "131             22.009293           419.631345           418.627090   \n",
       "261             33.523419           421.815420           420.969530   \n",
       "149             31.734696           426.264512           424.951447   \n",
       "\n",
       "     S-ZORB.TE_2003.DACA  S-ZORB.PDT_1003.DACA  S-ZORB.PDT_1002.DACA  \\\n",
       "111           413.883400              8.833203              1.592630   \n",
       "239           418.049318             10.232166              1.619074   \n",
       "131           417.115433              9.721973              1.659179   \n",
       "261           418.501955              8.802798             -0.086810   \n",
       "149           422.871210              4.665347              9.847435   \n",
       "\n",
       "     S-ZORB.PDT_3503.DACA  S-ZORB.PDT_3502.DACA  S-ZORB.PDT_3002.DACA  \\\n",
       "111              0.414316             10.840374              1.859845   \n",
       "239             -0.046673             12.297529              0.857222   \n",
       "131             -0.121192             14.540091              2.273573   \n",
       "261             -0.378456             11.761831              5.211471   \n",
       "149             -0.375334             13.312953              2.609494   \n",
       "\n",
       "     S-ZORB.PDT_1004.DACA  S-ZORB.PDI_2903.DACA  S-ZORB.PT_2901.DACA  \\\n",
       "111             16.262325              6.654529           545.758200   \n",
       "239              2.624593              6.405130           547.978245   \n",
       "131              3.047405              6.944564           549.017040   \n",
       "261             35.916541             37.113658           529.042520   \n",
       "149             42.312529             43.819674           537.495522   \n",
       "\n",
       "     S-ZORB.PT_2106.DACA  S-ZORB.TE_7508B.DACA  S-ZORB.TE_7506B.DACA  \\\n",
       "111             4.792891              7.413568              5.315188   \n",
       "239             4.803425             25.911597             25.492286   \n",
       "131             4.782526             29.868130             29.572823   \n",
       "261             5.804188             18.917353             17.721639   \n",
       "149             5.762571              9.973539              8.201709   \n",
       "\n",
       "     S-ZORB.PT_7505B.DACA  S-ZORB.TE_7504B.DACA  S-ZORB.PT_7503B.DACA  \\\n",
       "111              0.079719              7.140621              0.081644   \n",
       "239              0.176029             25.668823              0.175327   \n",
       "131              0.111675             29.660465              0.111580   \n",
       "261              0.064873             18.880591              0.065452   \n",
       "149              0.031015             10.124758              0.033004   \n",
       "\n",
       "     S-ZORB.TE_7502B.DACA  S-ZORB.TE_7106B.DACA  S-ZORB.TE_7108B.DACA  \\\n",
       "111              5.474902             52.090584             49.613284   \n",
       "239             25.586272             26.584718             26.713832   \n",
       "131             29.598133             56.450738             56.556588   \n",
       "261             18.009532             21.404255             20.884158   \n",
       "149              8.419809             10.897261             10.045660   \n",
       "\n",
       "     S-ZORB.PT_7107B.DACA  S-ZORB.PT_7103B.DACA  S-ZORB.PT_1604.DACA  \\\n",
       "111              3.075745              2.237385             0.179700   \n",
       "239              2.274992              2.269821             0.173732   \n",
       "131              3.013086              2.286089             0.167054   \n",
       "261              0.140376              0.099229             0.174473   \n",
       "149              0.015648              0.003383             0.165508   \n",
       "\n",
       "     S-ZORB.TC_1607.DACA  S-ZORB.PT_6005.DACA  S-ZORB.PT_6008.DACA  \\\n",
       "111           432.457522            -0.221964            -0.139021   \n",
       "239           449.576323            -0.175249            -0.073258   \n",
       "131           446.307435            -0.168473            -0.067553   \n",
       "261           358.565150            -0.350079            -0.245156   \n",
       "149           357.026378            -0.404606            -0.297383   \n",
       "\n",
       "     S-ZORB.PT_1601.DACA  S-ZORB.TE_1605.DACA  S-ZORB.SIS_FT_3202.PV  \\\n",
       "111             2.449868           409.125185             183.725845   \n",
       "239             2.495626           415.391458             186.913270   \n",
       "131             2.491996           412.212855             188.241373   \n",
       "261             2.568871           410.258838             305.601657   \n",
       "149             2.496320           411.150967             323.671690   \n",
       "\n",
       "     S-ZORB.TXE_3202A.DACA  S-ZORB.TXE_3201A.DACA  S-ZORB.TXE_2203A.DACA  \\\n",
       "111             358.456310             400.895607             484.919692   \n",
       "239             371.282495             411.768150             422.965307   \n",
       "131             372.693225             412.921870             418.532793   \n",
       "261             341.348000             386.741845             342.604172   \n",
       "149             275.942325             316.015278             351.280415   \n",
       "\n",
       "     S-ZORB.TXE_2202A.DACA  S-ZORB.TE_5008.DACA  S-ZORB.TE_5009.DACA  \\\n",
       "111             486.014535            69.642916            17.145213   \n",
       "239             423.259102            55.806230            35.423900   \n",
       "131             418.836008            65.673151            37.013230   \n",
       "261             343.682000            61.058466            28.717880   \n",
       "149             352.213132            53.049863            17.984170   \n",
       "\n",
       "     S-ZORB.FC_5001.DACA  S-ZORB.TE_1503.DACA  S-ZORB.AT-0001.DACA.PV  \\\n",
       "111          2482.262175             7.386963                4.053312   \n",
       "239          1186.417700            26.293875                0.520470   \n",
       "131          1698.779600            30.097203                0.571100   \n",
       "261          1639.313475            18.349903                0.565786   \n",
       "149          1284.308275            10.072203                0.545910   \n",
       "\n",
       "     S-ZORB.AT-0002.DACA.PV  S-ZORB.AT-0004.DACA.PV  S-ZORB.AT-0005.DACA.PV  \\\n",
       "111                5.799679                0.459793                0.525555   \n",
       "239                0.450679                0.464507                0.504073   \n",
       "131                0.453942                0.470241                0.501440   \n",
       "261                0.129716                0.632997                0.531441   \n",
       "149                0.096724                0.597686                0.466199   \n",
       "\n",
       "     S-ZORB.AT-0006.DACA.PV  S-ZORB.AT-0007.DACA.PV  S-ZORB.AT-0008.DACA.PV  \\\n",
       "111                0.479819                0.470983                0.430031   \n",
       "239                0.469449                0.453942                0.433258   \n",
       "131                0.496211                0.475823                0.432396   \n",
       "261                0.562543                0.733043                0.682877   \n",
       "149                0.560424                0.728496                0.692422   \n",
       "\n",
       "     S-ZORB.AT-0009.DACA.PV  S-ZORB.AT-0011.DACA.PV  S-ZORB.FT_1204.DACA.PV  \\\n",
       "111                0.471771                0.489661               75.141766   \n",
       "239                0.431468                0.492326               42.169189   \n",
       "131                0.460711                0.493490               28.385630   \n",
       "261                0.677623                0.647101               54.817995   \n",
       "149                0.658572                0.693177               40.053319   \n",
       "\n",
       "     S-ZORB.LC_5102.PIDA.PV  S-ZORB.TE_1102.DACA.PV  S-ZORB.CAL.LINE.PV  \\\n",
       "111               40.011234              423.929697            0.313991   \n",
       "239               38.995439              424.697885            0.289957   \n",
       "131               38.984290              422.535768            0.282758   \n",
       "261               44.956767              426.539975            0.281834   \n",
       "149               44.895846              429.980535            0.279306   \n",
       "\n",
       "     S-ZORB.CAL.CANGLIANG.PV  S-ZORB.CAL.SPEED.PV  \\\n",
       "111                30.271820             4.485089   \n",
       "239                24.325651             5.575779   \n",
       "131                22.987943             5.685402   \n",
       "261                22.871400             5.841039   \n",
       "149                28.266832             4.446526   \n",
       "\n",
       "     S-ZORB.FT_1503.TOTALIZERA.PV  S-ZORB.FT_1504.TOTALIZERA.PV  \\\n",
       "111                  1.201823e+07                   13658326.50   \n",
       "239                  7.480456e+05                    1077252.70   \n",
       "131                  2.032650e+06                    2811629.05   \n",
       "261                  1.036639e+07                   12505335.25   \n",
       "149                  1.714475e+07                   20987765.50   \n",
       "\n",
       "     S-ZORB.PC_1001A.PV  \n",
       "111            0.349741  \n",
       "239           -9.200040  \n",
       "131           -2.015496  \n",
       "261          -71.551618  \n",
       "149          -35.115716  "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_325.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data_325[feature_names]\n",
    "data = data.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RON损失</th>\n",
       "      <th>原料性质：硫含量</th>\n",
       "      <th>原料性质：辛烷值</th>\n",
       "      <th>原料性质：饱和烃</th>\n",
       "      <th>原料性质：烯烃</th>\n",
       "      <th>原料性质：溴值</th>\n",
       "      <th>原料性质：密度</th>\n",
       "      <th>待生吸附剂性质：焦炭</th>\n",
       "      <th>待生吸附剂性质：S</th>\n",
       "      <th>再生吸附剂性质：焦炭</th>\n",
       "      <th>再生吸附剂性质：S</th>\n",
       "      <th>S-ZORB.CAL_H2.PV</th>\n",
       "      <th>S-ZORB.FC_2801.PV</th>\n",
       "      <th>S-ZORB.FT_5101.PV</th>\n",
       "      <th>S-ZORB.FT_9001.PV</th>\n",
       "      <th>S-ZORB.LC_5001.PV</th>\n",
       "      <th>S-ZORB.LC_5101.PV</th>\n",
       "      <th>S-ZORB.PC_2105.PV</th>\n",
       "      <th>S-ZORB.PC_5101.PV</th>\n",
       "      <th>S-ZORB.PDT_2104.PV</th>\n",
       "      <th>S-ZORB.PT_2101.PV</th>\n",
       "      <th>S-ZORB.PT_2801.PV</th>\n",
       "      <th>S-ZORB.TC_5005.PV</th>\n",
       "      <th>S-ZORB.TE_2005.PV</th>\n",
       "      <th>S-ZORB.TE_2103.PV</th>\n",
       "      <th>S-ZORB.TE_2301.PV</th>\n",
       "      <th>S-ZORB.TE_5102.PV</th>\n",
       "      <th>S-ZORB.TE_5202.PV</th>\n",
       "      <th>S-ZORB.TE_9001.PV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.20</td>\n",
       "      <td>153.428571</td>\n",
       "      <td>85.3</td>\n",
       "      <td>58.50</td>\n",
       "      <td>17.6</td>\n",
       "      <td>45.150</td>\n",
       "      <td>720.80</td>\n",
       "      <td>2.45</td>\n",
       "      <td>8.85</td>\n",
       "      <td>1.27</td>\n",
       "      <td>6.69</td>\n",
       "      <td>0.302291</td>\n",
       "      <td>652.255985</td>\n",
       "      <td>737.834190</td>\n",
       "      <td>466.062710</td>\n",
       "      <td>55.040801</td>\n",
       "      <td>49.987329</td>\n",
       "      <td>4.795737</td>\n",
       "      <td>0.660073</td>\n",
       "      <td>81.158234</td>\n",
       "      <td>2.354010</td>\n",
       "      <td>2.467430</td>\n",
       "      <td>118.851450</td>\n",
       "      <td>415.880212</td>\n",
       "      <td>421.857275</td>\n",
       "      <td>374.109665</td>\n",
       "      <td>25.588707</td>\n",
       "      <td>34.683582</td>\n",
       "      <td>17.345706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.54</td>\n",
       "      <td>231.428571</td>\n",
       "      <td>90.1</td>\n",
       "      <td>50.40</td>\n",
       "      <td>23.4</td>\n",
       "      <td>43.820</td>\n",
       "      <td>735.15</td>\n",
       "      <td>3.48</td>\n",
       "      <td>10.67</td>\n",
       "      <td>0.90</td>\n",
       "      <td>6.35</td>\n",
       "      <td>0.232117</td>\n",
       "      <td>651.170082</td>\n",
       "      <td>1254.662175</td>\n",
       "      <td>540.493378</td>\n",
       "      <td>46.019762</td>\n",
       "      <td>556.221002</td>\n",
       "      <td>4.798732</td>\n",
       "      <td>0.660179</td>\n",
       "      <td>65.193053</td>\n",
       "      <td>2.401949</td>\n",
       "      <td>2.504474</td>\n",
       "      <td>128.249900</td>\n",
       "      <td>420.478555</td>\n",
       "      <td>423.964413</td>\n",
       "      <td>306.001070</td>\n",
       "      <td>33.124049</td>\n",
       "      <td>36.897491</td>\n",
       "      <td>29.282571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.61</td>\n",
       "      <td>254.428571</td>\n",
       "      <td>89.6</td>\n",
       "      <td>54.80</td>\n",
       "      <td>22.1</td>\n",
       "      <td>45.820</td>\n",
       "      <td>738.70</td>\n",
       "      <td>3.45</td>\n",
       "      <td>7.44</td>\n",
       "      <td>1.35</td>\n",
       "      <td>6.25</td>\n",
       "      <td>0.248665</td>\n",
       "      <td>699.109595</td>\n",
       "      <td>974.489215</td>\n",
       "      <td>525.719345</td>\n",
       "      <td>54.993771</td>\n",
       "      <td>558.620155</td>\n",
       "      <td>4.777457</td>\n",
       "      <td>0.659932</td>\n",
       "      <td>61.651206</td>\n",
       "      <td>2.398573</td>\n",
       "      <td>2.497041</td>\n",
       "      <td>130.969347</td>\n",
       "      <td>419.326405</td>\n",
       "      <td>422.312170</td>\n",
       "      <td>304.170097</td>\n",
       "      <td>39.659723</td>\n",
       "      <td>36.630371</td>\n",
       "      <td>34.610186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.70</td>\n",
       "      <td>296.714286</td>\n",
       "      <td>90.1</td>\n",
       "      <td>47.54</td>\n",
       "      <td>30.4</td>\n",
       "      <td>47.795</td>\n",
       "      <td>733.60</td>\n",
       "      <td>1.97</td>\n",
       "      <td>4.70</td>\n",
       "      <td>1.30</td>\n",
       "      <td>3.71</td>\n",
       "      <td>0.251655</td>\n",
       "      <td>749.973385</td>\n",
       "      <td>756.719975</td>\n",
       "      <td>445.088357</td>\n",
       "      <td>49.170634</td>\n",
       "      <td>652.637630</td>\n",
       "      <td>5.796858</td>\n",
       "      <td>0.650195</td>\n",
       "      <td>61.303989</td>\n",
       "      <td>2.463150</td>\n",
       "      <td>2.563977</td>\n",
       "      <td>130.141368</td>\n",
       "      <td>421.780680</td>\n",
       "      <td>424.563570</td>\n",
       "      <td>308.704093</td>\n",
       "      <td>29.769675</td>\n",
       "      <td>33.081298</td>\n",
       "      <td>24.469261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.71</td>\n",
       "      <td>307.285714</td>\n",
       "      <td>90.2</td>\n",
       "      <td>53.60</td>\n",
       "      <td>25.9</td>\n",
       "      <td>58.110</td>\n",
       "      <td>721.80</td>\n",
       "      <td>9.37</td>\n",
       "      <td>12.19</td>\n",
       "      <td>2.47</td>\n",
       "      <td>8.84</td>\n",
       "      <td>0.263415</td>\n",
       "      <td>757.935920</td>\n",
       "      <td>730.613335</td>\n",
       "      <td>421.129715</td>\n",
       "      <td>50.015678</td>\n",
       "      <td>643.764740</td>\n",
       "      <td>5.763151</td>\n",
       "      <td>0.659987</td>\n",
       "      <td>75.787407</td>\n",
       "      <td>2.381479</td>\n",
       "      <td>2.498833</td>\n",
       "      <td>125.809107</td>\n",
       "      <td>425.822545</td>\n",
       "      <td>428.609537</td>\n",
       "      <td>255.761750</td>\n",
       "      <td>28.324245</td>\n",
       "      <td>31.850250</td>\n",
       "      <td>17.155943</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RON损失    原料性质：硫含量  原料性质：辛烷值  原料性质：饱和烃  原料性质：烯烃  原料性质：溴值  原料性质：密度  \\\n",
       "0   0.20  153.428571      85.3     58.50     17.6   45.150   720.80   \n",
       "1   0.54  231.428571      90.1     50.40     23.4   43.820   735.15   \n",
       "2   0.61  254.428571      89.6     54.80     22.1   45.820   738.70   \n",
       "3   0.70  296.714286      90.1     47.54     30.4   47.795   733.60   \n",
       "4   0.71  307.285714      90.2     53.60     25.9   58.110   721.80   \n",
       "\n",
       "   待生吸附剂性质：焦炭  待生吸附剂性质：S  再生吸附剂性质：焦炭  再生吸附剂性质：S  S-ZORB.CAL_H2.PV  \\\n",
       "0        2.45       8.85        1.27       6.69          0.302291   \n",
       "1        3.48      10.67        0.90       6.35          0.232117   \n",
       "2        3.45       7.44        1.35       6.25          0.248665   \n",
       "3        1.97       4.70        1.30       3.71          0.251655   \n",
       "4        9.37      12.19        2.47       8.84          0.263415   \n",
       "\n",
       "   S-ZORB.FC_2801.PV  S-ZORB.FT_5101.PV  S-ZORB.FT_9001.PV  S-ZORB.LC_5001.PV  \\\n",
       "0         652.255985         737.834190         466.062710          55.040801   \n",
       "1         651.170082        1254.662175         540.493378          46.019762   \n",
       "2         699.109595         974.489215         525.719345          54.993771   \n",
       "3         749.973385         756.719975         445.088357          49.170634   \n",
       "4         757.935920         730.613335         421.129715          50.015678   \n",
       "\n",
       "   S-ZORB.LC_5101.PV  S-ZORB.PC_2105.PV  S-ZORB.PC_5101.PV  \\\n",
       "0          49.987329           4.795737           0.660073   \n",
       "1         556.221002           4.798732           0.660179   \n",
       "2         558.620155           4.777457           0.659932   \n",
       "3         652.637630           5.796858           0.650195   \n",
       "4         643.764740           5.763151           0.659987   \n",
       "\n",
       "   S-ZORB.PDT_2104.PV  S-ZORB.PT_2101.PV  S-ZORB.PT_2801.PV  \\\n",
       "0           81.158234           2.354010           2.467430   \n",
       "1           65.193053           2.401949           2.504474   \n",
       "2           61.651206           2.398573           2.497041   \n",
       "3           61.303989           2.463150           2.563977   \n",
       "4           75.787407           2.381479           2.498833   \n",
       "\n",
       "   S-ZORB.TC_5005.PV  S-ZORB.TE_2005.PV  S-ZORB.TE_2103.PV  S-ZORB.TE_2301.PV  \\\n",
       "0         118.851450         415.880212         421.857275         374.109665   \n",
       "1         128.249900         420.478555         423.964413         306.001070   \n",
       "2         130.969347         419.326405         422.312170         304.170097   \n",
       "3         130.141368         421.780680         424.563570         308.704093   \n",
       "4         125.809107         425.822545         428.609537         255.761750   \n",
       "\n",
       "   S-ZORB.TE_5102.PV  S-ZORB.TE_5202.PV  S-ZORB.TE_9001.PV  \n",
       "0          25.588707          34.683582          17.345706  \n",
       "1          33.124049          36.897491          29.282571  \n",
       "2          39.659723          36.630371          34.610186  \n",
       "3          29.769675          33.081298          24.469261  \n",
       "4          28.324245          31.850250          17.155943  "
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(268, 29)"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+PnuzUlNTOeGEE1i/fj2XXHIJ06ZN26chSHd3d7B0sb29nYyMDM455xwAkpKSmD17NrW1tSxcuJAbbrgBgLKyMiZPnszGjRs56qijBlz/qFGj+MlPfgLABx98wOeff85LL70U/HpHRwcAM2bM4A9/+ANLly4FYM+ePXzxxRcANDQ0DPt5HKpBBWQul+tMIN+yrCUul+t4YLFlWf8nsksTiTC7oceYEvAW9n8sIiIiEi1DyGSFW11dHTNmzGDq1Kk88MADVFdXk5SUREFBAXPnzsWyLG677TZmzpxJTk4Ojz76KHPmzCElJYWnn36ad999l23btnHttddSVVUFQElJCUuXLuXrX/96MEBLSUnh9ddfB2Dnzp1MmzYNt9vNyy+/zB133MHChQv5+9//HgygAAoLC9m8eTNTpkw56PewcuVKVqxYwc0330xlZSWPPfYYOTk5bN++nQsuuAC/38+RRx65z7lra2t5+OGHg8+B3ZhkpBwyIHO5XG7gIeB1l8v1DaAQuMjlcp0NbASutSyr92DnEIlJdsv77InmjzJkIiIiksA+/vhjrrjiCmbOnMlxxx3Hjh07SE9Px+VycdVVV/HII49w0kkn0dvby+WXX878+fP58MMPmTlzJikpKSxatIgLL7xwv/MuWLCABQsWDFiyuHnzZmbPnh3c3/XSSy/xox/9iLy8vJDa5j/++OOcd955XHDBBbjdbt5//30ATj/9dP7+978za9Ysbrnlln3uM378eC699FIAPvzwwyE/5nANJkM2H/gUuAP4N6ATmG1ZVq3L5XoSuAB4JXJLFImQ5kpISgFPPngnwra3o70iERERkahoa2tj69atZGZmMnfuXO6//362bdsGgMfj4bLLLmPx4sV4PJ7gvqwnn3wyeP9f/epXpKWlBT+2LCv4JxAIkJycHPxaIBAATOniypUreeihh3j77bd58MEHOfnkk7nrrrv45JNPuOOOO4L3qa6uZvr06QctWdy5cyfr16/noYceYs6cOTz22GNMnjyZkpISGhoa+MlPfoLX6w2uLxAI4Pf78Xq9nHHGGYDZPwemzf/ea46kwQRkxwF/siyrzuVyPQX8yrKs2r6vrQX2a3vicrkWAgsBJk6cGK61ioSXrwK8RZCUbDJkrbXQ2wUpaYe+r4iIiEgcWbZsGfPmzWPjxo3cd999tLa2cuedd/LUU09x+umnk52dTUpKCklJSXR3d9Pb27tPW/ru7m66u7uDH3d1ddHV1cWGDRu46aabgre99NJLCQQC3HTTTaSlpfHd736X0tJSbr31VmbNmsW9995LSkoKa9asYd68eTzzzDMUFRVRUlJyyMHUGzdu5Nvf/jbr16/nhhtu4Oqrr+buu+/G5XLx5ptvcvHFF/Od73yH73//+3R1ddHY2MgFF1xATk4Ot912W/A8a9asobe3l6uvvjq8T/IBuA71jblcrn8Hui3Lut/lcv0zcBlwG7AJeBMToB2wFcqJJ55orV27NnwrFgmXh881wdeCV2H9/8JL18O/rYNxh0V7ZSIiIpJANm/ezPTp06O9jKjp6enB7/fvU8oIJou192yzoRjOfYdroH9Pl8v1kWVZJw50+6RBnPMR4GyXy7UM+AHwB+DPwHpg1cGCMZGY5quA7Enm79kT+z8nIiIiIiPG7XbvF4wBwwqoohWMheKQJYuWZbUCV3zp0zMjsxyREdLbBW11kF1sPvb2HZvVaVFERERGXjQzOhI+h6o+HMhgMmQi8afZtGINZsayCsGVrAyZiIiIjLj09HSamppCejMvscOyLJqamgbM9h3MoAdDi8QVO/CyM2PJKZA1QbPIREREZMQVFRVRVVXFzp07o70UGab09HSKioqGdB8FZJKY7IAse68uoJpFJiIiIlHgdruZPHlytJchUaKSRUlMzZXgSjJZMZu3WHvIRERERGREKSCTxOSrMPvGkt39n8ueCC3V4O+J3rpEREREJKEoIJPE5Kvct1wRTMdFKwAtNdFZk4iIiIgkHAVkkph8Ff0NPWyaRSYiIiIiI0wBmSQefw+01uyfIdMsMhEREREZYQrIJPG0VJvSxOwvZci8RYBLGTIRERERGTEKyCTxDNTyHiAlDTwFCshEREREZMQoIJPEYw9//vIeMjBZMwVkIiIiIjJCFJBJ4vFVAK6+EsUv0XBoERERERlBCsgk8TRXgifflCh+mbfY7DEL+Ed+XSIiIiKScBSQSeLxVey/f8yWPRECvdBaO7JrEhEREZGEpIBMEs9AM8hsdudFn1rfi4iIiEjkKSCTxBLwm5LEA2bIJpmj9pGJiIiIyAhQQCaJpbXWlCR+eQaZzW700ayATEREREQiTwGZJJYDzSCzuTMgM1cZMhEREREZEQrIJLEEZ5AdICCDvllk2kMmIiIiIpGngEwSSzBDdoCSRdAsMhEREREZMQrIJLE0V0BmjilNPBBvMTRXQSAwcusSERERkYSkgEwSy8FmkNmyJ4K/C9obRmZNIiIiEro1D8ODZ0V7FSIhU0AmicVXObiAzL6tiIiIxLZNL0Lteuhqi/ZKREKigEwSRyAAzZUHHgptCwZk5ZFfk4iIiISupxOq1pq/t9VHdy0iIVJAJomjvQH83YfOkNkBW7MyZCIiIjGteq3ZZgBm1qiIAykgk8RxqBlktrTRkDFWnRZFRERiXdmK/r+31kVvHSLDoIBMEsdgAzLQLDIREREnKFsBY0rM35UhE4dSQCaJww7IDrWHDDSLTEREJNb1dkHVGjj8AnCPUoZMHEsBmSQOX4UpRUwbfejbZk8yt7esyK9LREREhq76I+jthElfBU++MmTiWArIJHE0V5pSxMHwFkPvHuhoiuyaREREJDRlKwEXTDodPAXKkIljKSCTxDGYodA2tb4XERGJbeUrIG8GjBqrDJk4mgIySQyWZZp0eAcbkPVl0tTYQ0REJPb0dkPlh6ZcEfozZNpqIA6kgEwSQ3ujKUEcbIbMbvyhxh4iIiKxp6YUejqg5Azz8eg883FXS3TXJRICBWSSGJrtlveD3EOWkQ1pXg2HFhERiUXlffPH9s6QgfaRiSMpIJPEMJQZZDa1vhcREYlNZSshZzpkjjMfe/LNUfvIxIEUkElisPeCDWYGmU3DoUVERGKPvwcqVkPJV/s/pwyZOJgCMkkMvgpTgpiRPfj72BkybRAWERGJHbUfQ097//4xAE+eOSpDJg6kgEwSw1BmkNm8xdDdCp2+yKxJREREhq7sS/vHANI8kOpRhkwcSQGZJIahzCCzBWeRaR+ZiIhIzChfCeOnwejcfT+vWWTiUArIJP7ZM8iGHJBpFpmIiEhM8fdC+ap9s2M2T74yZOJICsgk/u3ZbUoPh9LQAyB7kjkqQyYiIhIb6jaY3+l77x+zeQqUIRNHUkAm8c+eJTbUDFnGGHBnahaZiIhIrChfaY4DBmR9GTI14xKHUUAm8c83xKHQNpdLs8hERERiSdkKGHtY/9yxvXkKwN9tKmNEHEQBmcS/YEA2aej3zS5WQCYiIhILAn6zf2yg7BhoOLQ4lgIyiX++SlN6mDFm6PdVhkxERCQ21G+CruaDBGT2cGgFZOIsCsgk/tkt712uod/XW2zmkHW2hH9dIiIiMnhlffvHBuqwCHtlyNRpUZxFAZnEv+aKoe8fs9mNQNTYQ0REJLrKVsCYEvAWDvx1lSyKQykgk/gXylBom1rfi4iIRF8gABXvH7hcEcCdAenZypCJ4yggk/jW2Wz+DHUGmU3DoUVERKKv4VPTPXHSQQIy6JtFpoBMnEUBmcQ3X4gzyGyZOZCSDr7y8K1JRELX02k6rYlIYgnOHzvA/jGbJ18li+I4CsgkvoU6FNrmcpnsmvaQicSGP50Fy+6M9ipEZKSVLQfvxEP/PleGTBxIAZnEt+AMshADMvu+2kMmEn0BPzR+BnUbor0SERlJlgXlh9g/ZvPkm4AsEIj8ukTCRAGZxDdfhSk5zMwJ/RzZxdpDJhIL9vjACihjLZJodm6BjqZDlyuCyZBZfuhojPy6RMJEAZnEN1+FKTkMZQaZLXuieWHvbg/fukRk6DqazLG5OrrrEJGRVbbCHA80f2xvan0vDqSATOJbc+XwyhXB1KwDNFcNfz0iEjo7IOtoNM09RCQxlK2ArCIzg+xQPAXmqH1k4iAKyCS++YYxFNpmB3TaRyYSXXuXILUoSyaSECzLdFgs+ergql2CGTIFZOIcCsgkfnW3myvqw82QBWeRKSATiSo7QwbKWIskisbPoX3n4MoVAUbnmaMCMnEQBWQSv+xGHN5hBmSj8yHJrYBMJNralSETSThly81xMB0WAVJSYdR47SETR1FAFi8+egI2PBftVcSW4c4gsyUlgbdInd2+zN8DO5ZHexWSSDp2QXKa+bsae4gkhvKVZl/Y2CmDv49mkYnDKCCLF0tvhw8eiPYqYouv3ByHu4cMNItsIJ+8BE9cBI1fRHslkig6GsGTZ65+t6hkUSTuWRaUrTTlikPpluzJV4ZMHEUBWTxoqTUvPMrg7MtXaUoNR+cP/1yaRba/XdvN0VcW1WVIAuloMsGYt1B7yEQSQdM2aKsb3PyxvdnDoUUcQgFZPKhdb45t9WoFvTdfhSk1TArDj3n2JPNLQc9vP/sCQEtNdNchiaO9EUaNM+2vVbIoEv/K++aPlZw5tPt5CqC9Afy94V+TSAQoIIsH1ev6/66N7v18FcPfP2bz9pU96qp8PwVkMtI6dkHmeHOhRa91IvGvbCVk5sK4rwztfp58sAKmO6OIAyggiwc1peDq+6dU2WK/5srw7B+D/sCuWfvIguzgVAGZjJSOvgyZtxC6WqCzOdorEpFIGer8sb0Fh0NrH5k4gwIyp7MsE5DZ8zm0z8no6TQlnNmTwnM+zSLbl2UpIJOR1d0BPR19JYuF5nMqWxSJX7t3mEz4YOeP7U3DocVhFJA5XXOluWp8xIUmS6YMmWEHC94wZcg8E8CVrIDX1t4IvX376RSQyUjYs8scR40zJYugskWReFa20hyHun8MlCETx1FA5nQ1peZYdLJ5AVLAYARb3odpD1lyirkqrwyZYQf+ngJoVUAmI8AeCr13QKY9nSLxq3yl6aqac/jQ75uZYy5SK0MmDqGAzOlqSk1r9/yjTDZIGTIjOBQ6TBkyMMGdnl/Dfh6KT4E9u005mUgkdTSZY+Z4M8rClaQMmUg8K1sJk04f+v4xMBdRM3OVIRPHUEDmdNXrIO9ISEkzwYcCBsNXYUoMPRPCd04Nh+5nZyaKTzFH/dKTSLMDslHjzJstT4H2kInEq93lpolWyRmhn0OzyBKT3VvBYRSQOZllQc16mHCc+djbN5snEIjuumKBr9KUGCanhO+c2cUm8OjtDt85naq5CtyZ5mIAaB+ZRN7eARmY/9+6ACUSn8rt/WPDCcgKFJAlkp1b4e1fwv/MhD/NgoYt0V7RkITx3aqMuF3boasZJhxvPvYWQ6DHDDDOCmNmyInCOYPMlj3RzDVpqYaxk8N7bqfxVZgA1e52p4BMIq290WS907PNx94iqF0f3TWJSGSUrYSMMZAzPfRzePKhak341iSxp6UWNr0AG56Bug2mlH3K2XD2f4Z3y8oIUEDmZHZK1s6QBWdlVSkga66EyWeF95zB4dCVCsiaq8wbYruTlfbySKR1NMGosZDUV9jhLYStr5tKgVD2mIhI7CpbbtrdJw2jkMtTYLpQ93ZDSmr41ibR1dkCm5eYIGzHMsAyiYnzfg0zLgNPXrRXGBIFZE5WUwop6ZDbdwXJu9esrOKTo7euaOvtNhmbcF8dsQNe7SMzAdmEYyFtNKR7lSGTyLOHQtuyiszohY4m0+hDROJDc5XplHzq9cM7jz2LrK3ecdkS+ZLebvjiLdj4LGz9m3ntHzMZzroFjr4Sxn8l2iscNgVkTlZTCvlHQ7LbfBxsBZ3g+ypaqgEr/CWLWYWAS6MFujvMm2P7AkBWoZp6SOR17DItsG1eezh0pQIykXhizx8LZSD03oKzyOoUkDlRIACVH5gg7JO/mo7Oo8bB8fNNEFZ0YlxVRyggc6qA3zT0OO5b/Z9LG21qrhM9YLAzWOEaCm1LSTWloImeIbPLE+3n11OgkkWJvPbGfecRBS9AVfeXbYuI80au8oAAACAASURBVJWvMJUXeTOGdx67dE0XDJ2lYYsJwjY8ZzptukfBEReaIOyws/uTEHFGAZlTNX4OPe37vxHRLLK9ZpCFOUMGen6hPyC1rzhmTYD6TdFbjySGjqb9SxZBFwNE4k3ZCph4OiQlD+88e2fIJLa11MKm52HDs/3NOQ47B875qQnG0kZHe4URp4DMqYINPY7f9/PZE033xUTmqwBc/R0Awyl7IlSuDv95ncSeQWZnKLIKoa0B/D1xe+VKoiwQgD279i1NzBwPyWn9P48i4nwtteY9zInfH/65Ro03nVmVIYtNnc19zTme/VJzjt/AUZfB6Nxor3BEKSBzqpp1Zg7U+Kn7ft5bBNvfS+zOY75Kk7WJRFel7GL45EXw94Z3xpmTNFeZq1f21cesAsBSnb5ETqfPjJzYO0Pmcpn/5wrIROJHcP7YMPePgenQqOHQsaW3G7540wRhW/8G/q6+5hz/B46+Ii6ac4QqQd9RxoGaUig4Zv+UvrcYulvNG5iMMdFZW7T5KsK/f8yWPRECveaKW6IGH82V4JnQnw3bexZZoj4nElnBodBfat7hLVLJokg8KVsOaVmQPzM85/PkK0MWKzY8C3+7pa85x3g44Tsw8yooPCFxEwh7UUDmRP4eqNsIJ12z/9fsN8S+ysQOyCaeGplz7z2LLFGDD3sGmc2eedeq1vcSIe2N5jhq7L6f9xbBjuUjvx4RiYyyleb393D3j9k8BdC0LTznktA1fg6vLIL8o0w2bMosbXH4kkFP3HO5XPe7XK6L+/7+iMvlWuVyuX4auaXJATVsNjMYBuosFgwYErSMx99rrphHKljKnmSOidxp0Vex7/MbHA6tgEwixM6Qfbm9vT1ywd878msSkfBqrYemz6HkjPCdUxmy6PP3wIsLwZ0BVz0FU89VMDaAQQVkLpfrTCDfsqwlLpfrMiDZsqzTgCkul2vqIe4u4RZs6HGwgCxBOwG21oDlj0yHRejPDCVqQBbwm8Br7wxZxhhIyVBAJpHTYWfIxu37eW+h+f/epj0iIo5n7x+bFOaArNMHPXvCd04ZmuW/M30PLrqrf1i37OeQAZnL5XIDDwFlLpfrG8As4Nm+L/8D2O9/jsvlWuhyuda6XK61O3fuDONyBTABWZoXxk7Z/2uZ482b40QNGOwZbJHaQ+ZOh9F5ifv8tjVAoGffgMxurqC9PBIpwT1kXw7I7AtQ+tkTcbyyFZA62uyPDxe1vo+u6o/gvTvMXrEZl0Z7NTFtMBmy+cCnwB3AycAPAfu33y4g78t3sCzrT5ZlnWhZ1ok5OTnhWqvYatbBhGMH3gTpcpk3y4maIQvOyJoUucfwFiduQGb/XHm/lIHMmmDaFYtEQnuT6Srrztj388GGMglaoi0ST8r79o+Fs4OxnZFRQDbyevbAi9eaf4Pz74j2amLeYAKy44A/WZZVBzwFLAPs34qjB3kOCZeeTqj/dOByRVt2ceLuIQsGDEUHv91wZE9M3ID3QM9v1gSVLErkdDRB5rj9P+/tC8iUIRNxtradsHMLTApDu/u9BTNkumA44t66zewJvPR+yMiO9mpi3mCCqS8AuzbuRKCE/jLFY4CysK9KDqzhE1MyVnj8gW/jLeov3Us0vnJTUuhOj9xj2AFvIBC5x4hVvoMEZK01ifmcSOR1NO5frgiQ7oVUT+JegBKJF8H5Y2HcPwYqWYyWbe/CBw/AKdeZjopySIPJCz8CPOpyua4G3Jg9ZK+4XK4JwPlAhPqLy4Cq15njwTJk3onQ3mCyaZEMTGKRrzJy+8ds2RPB3w1t9X1DkRNIc5V5E5yete/nswrNfLaORhidG521SfzqaBo4IAPNIhOJB+UrwT3q4O9tQpExBpJTlSEbSXt88PIPYfw0mH1btFfjGIfMkFmW1WpZ1hWWZX3NsqzTLMsqxwRlq4GzLctqjvQiZS81680bk4MFHdkJ3PreVxG5Dou2RG5931w18M9esPW93hhLBHQ07T8U2uYtTMzXOpF4UrYSik8Jfzt0l6uv9b0yZCPm9f8wF6znPLj/vl85oJD2f1mWtduyrGf79pXJSKophQnHH3yqeaK2vg8EzBuzSAdkifr8gvmeBwrI7OHQ2kcmkdB+kAxZVqEuBIg4Wccusx2jJMz7x2yeAmXIRsonf4WNz8LXbjn41hrZjxpyOEl3O+zcfOiUvr2/J9EChrY6s78uUkOhbfb5feWRfZxY1Fw5cMOUYLc7BWQSZj17oKd94KYeYH4e23eaEm0RcZ5IzB/bmyffZGwkslrr4NUfQeEJcOZN0V6N4yggc5K6jWAFDh2QZU0AV1LiNfawv99ItrwHSM00V+sT7fntbIHO5oEDsswcSEpRQCbhd6AZZLbgxQBlyUQcqWylmZ8aqYyKp0Ali5FmWfDyv5oLY3MeDO/oggShgMxJakrN8VABWbIbPBMSL0Nm7+mKdFMPMGWRibaHzN6nM1AGMinJ/NJTQCbhFgzIDrSHrO8CgQIyEWcqXwHFJ0FKWmTO78mHrhboaovM+QU+egy+eBPO/QWMnxrt1TiSAjInqV5n3vQOprNfdnHiZXCa7aHQIxCQeYsTL+C1A7IDBbxZE/SmWMKvvdEcD9ZlETSLTMSJ9uyGuk2RK1eE/qZTKluMjKZt8MZ/wpSz4aRror0ax1JA5iQ1pYNvCestSryAwVdh3rSlZkb+sbInmoDXsiL/WLGi+RAZyKwJ2jgt4dexyxwzD5AhCzaUUadFEccpXwVYkWvoASZDBvr9FAn+XvjrdaYy69L7TbWMhETPnFN0tpiJ5xMGWWPtLTbZioA/suuKJb7KyHdYtGVPhN49/VfvE0FzFSS5zeDtgXgmmJLFRApSJfI6DpEhc2eYr6n1vYjzlK+E5DQoPDFyj6Hh0JGz8g9Q9SFc+Pv+i2MSEgVkTlG73hwHmyHLLjaDehPpBchXMTL7x6A/8EukfWS+SvOCe6ArYFkToKcDOn0juy6Jbx1NpklRevaBb+MtUsmiiBOVrYCik8CdHrnHUIYsMmo/hqW3w4zL4OhvRns1jqeAzCkG29DD5u0LGBKlbNGyzPc6Uhmy4CyyBArIDjXjLVg6pl96EkYdTZAx9uClMFlF2r8o4jSdzVC3IbLligBpWeAelVgXqCOtpxNevNY0W7rwd9FeTVxQQOYUNaXmzfCBZvF8WXCje4KU8bTvhN7OESxZtGeRJVhANlDLe5uGQ0sktDceuFzR5i1UhkzEaSpWm1E+kyIckLlcJkumDFn4vPNLMxf3G/fBqLHRXk1cUEDmFNXrBp8dg8QLGOzvc6QCsnSv+ZMoz6+/B1prDl4SGgzI9MZYwqhj14EbetiyCqGr2ey1FRFnKFsByammZDHSNIssfMpWwKr74MTvw9TZ0V5N3FBA5gQdu8BXPrSALDXTlPkkSsniSM4gs9mdFhNBa625knmwDNnofMClq5ASXh2Nh74Cq1lkIs5TvhIKT4DUUZF/LGXIwqOzBf56PYydAv/fL6O9mriigMwJgvvHhjjFPpFmkflGcAaZzZtAw6Htn6ODBWQpqTA6N+xvii3LYtlnO+no7g3recUhOpoOPBTapllkIs7S1Qo16yNfrmizM2TqAjw8f/+xGTEy58GRGTGUQBSQOUHNOnMsOGZo9/MWJ84esubK/jLCkZI90TxuIrzA2z9HhyoJ9RSEfQ/Zii8amf/oh7y8XnvTEk4gYCoEDrWHLKvQHDWLTMQZKj4Ayw8lERwIvTdPvukC3KWy5pBtfhXWPw1n3gTFI1BmmmAUkDlBzXoYexhkHKTt80C8xYkTMPgqRm7/mC27GLrbYM/ukX3caLBLX+03vgeSVRj2gOz+d7cBUOvbE9bzigN0+sybtkPtIfMUmNb4iXIBSsTpyldAUgoUnzwyj6dZZMPTthOW3GASA1+7JdqriUsKyJygphQKh1iuCIkVMPgq+1v9j5REmkXWXGnKxg5V6581IawBWWnFblZtbwKgvqUrbOcVh+gw//aHzJAlp5g3XCpZFHGGshVmG8ZIlb1pFlnoLAuWLDJlpnP+ZLYnSNgpIIt1rfVmT85QGnrYgrOy4nwfmWVFJ0PmTaBOlodqeW/LKjBZje72sDzs/Uu34c1wM2V8Jg2tnWE5pzjIYAMy6MvOKkMmEvO6282F5kjPH9ubMmShK30Ktr4Os/8Lco+I9mrilgKyWDfUgdB7sxtcxHsZz57d0NMehZLFBBq+7ascZEBm7+UZ/lXIz+pbefPTer5zegkl4zOVIUtE7Y3mOJiATLPIRJyh8gMI9I7c/jGA0XnmqAzZ0OwuM408Ss6EU66P9mrimgKyWFdTavZG5M8c+n2DGZw4Dxh85eY4kh0WATLGQKon/jNklmWC+sEEvPYsstbhly0+sHQbGe5kvnt6CbmeNBpaFZAlnCFnyKoTY8+siJOVrQRXMhSfMnKPmTYa0rKUIRuKgN+0uHclwaV/hCSFDJGkZzfW1ayD8YebF5OhGjUOUjLiP4NjB5wjnSFzuRJjtICdgRxMhsxjD4ceXkBWuauDlz+uYe7JExmTmUpuVjpN7V30+gPDOq84zFACMm8x9Hb230dEYlPZCphwLKR5RvZxNYtsaFbdCxXvw/l3jPwF7wSkgCyWWZbJkIVSrgh7BQxxnsGJxlBoW3YCzCKzA/rBPL9ZfXX6w5xF9tDy7SS54F++NhmAXE8algWNbd3DOq84TEcTuEcNbnCst69cNt5LtEWcrLsDqj8a2XJFmydfGbLBqv8E3vl/MP1iOObqaK8mISggi2Ut1dC+M7QOiza79X08a640pYMZY0b+sb3F0BzvAVnfG9zBZMhSMyE9e1h7yHa2dvHMmkrmHFdIgTcDgLysdAA19kg0gxkKbQvuX9Q+MpGYVbUGAj0wKRoBWYEyZIPR2wUvXmt+l1/0B3NxXyJOAVksq+4bCB1qhgzMm+h4v2LsqzCZwGi8aGRPhM5m8yde+YaQIYNhzyJ7bOUOuv0Brj3rsODncj1pgFrfJ5z2Rhg1dnC3tS8YxPvrnYiTla0we5Imnjryj21nyLTP9OCW3g71G+GSew49A1LCRgFZLKspNYMT844K/RzZxSbL1hPHQ3V9lSO/f8yWnQCNU5orISV98C/MWQUhZylaOnv486pyzj8qn8Ny+vdNxluG7J63P+eC/1lOjYZdH1xH0+B/7kaNh+Q0BWQisax8pWlSlp418o/tKQB/d2LMZg1VxWpY+T9w/Hw4/LxoryahKCCLZTWlkHskuNNDP4c9LDme36T4KqKzfwwSYzi0PYNssBnIrAkhl4U8tbqc1q5efjDrK/t8fvzoVFyu+MmQrSnfzae1LXzzj++zbWdbtJcTuzoaB9fQA0wHsKwJKlkUiVU9nVC1Njr7x0DDoQ+lqxX+eq15P/X1X0V7NQlHAVmsGm5DD1t2nA8v3uODruboZci8CTCLrLlyaAFvViG0NUDv0BpwdPb4eXTFDs6cOp6jCr37fC0lOYlxmWnsjJMMWUNLJ0fke+j2B7jigVVsqo7jktfh6Ng1+D1k0FeirYBMJCZVrwV/VxQDMns4tAKyAb3xn7C7HOY8OPIdMEUBWczavQM6fcMPyOJ9X4UdCEWrJWvmeDNaIF4DXujPkA2WpwCwoG1o3ayeW1tJY1v3ftkxW64nLW4yZHUtnZxUMpbnrjudDHcyV/9pNau2qV37Pno6obtt8HvIoH8WmYjEnrIVgAsmnhadxw9myNRpcT+fvQHrnoCvLoJJUfr3SXAKyGJVTak5DqfDIpi5UK7k+M3g2IFQtDJk8T5aoKcT2uqHniGDITX26PUHeHDZdo6bmM2pUwZ+A56blRYXe8g6e/z4OnrIy0pj8vhMnr/+NAq86XznsQ/5xyd6oxBkzxMbyqZyb5H5uQv4I7MmEQld2QrIPwoysqPz+KNVsjig9iZ4+V9Nv4Kz/zPaq0lYCshiVfU6s0E9Z/rwzpOcYvZVxGvTiWAHwCgFZBDfs8jsbMNQMpBZQx8OvWRDDVW79/CDWV/BdYC9anme9LjIkDX0fQ92o5ICbwbPXnsa0wuyuP7pdTz/UZxms4eqo9EcB7uHDMwsMsuvK+Aisaa3y7S8Lzkzemtwp5vxOHp92Ncbt5qKrDkPQkpatFeTsBSQxaqa9eZKUkrq8M8Vz7PIfBWmZDCarVm9cZwhG8oMMltwOPTgArJAwOKPS7cxLW80/3RE7gFvl5uVRlNbF73+wODXEoPq+7J8dkAGMCYzlaevOYVTp4zl5uc+5uHl26O1vNhhZ8iGEpBl9f2cqmxRJLZUr4PeTpj01eiuY7SGQ+/DsmDr383w5/xhdPSWYVNAFosCAahdDxOGWa5o8xbFb0DWHMUZZLbsibBnF3TFYbe85iHOIAMzTNI9atAB2dtbGvisvo3rZx1GUtKB/x1zs9IJWNDUPrRmIbGmrtkEZPnefbunjk5L4dEFJ3H+Ufn8v9c2c+cbW7ESeV5Oxy5zHFJTj75y2XjdMyviVGUrzHHS6dFdhydfJYt7a640jdEKjo32ShKeArJY1PS52cw+3IYetuzi+N1X4auI3v4xW3Ycd1psrgJc/WWIg+Hqu33roQMyy7K4f+kXFI3J4OKZB38Mezh0g8PLFutb+jJknv3HWaSlJHPvvOO56sRi7n33C3760ib8gQQNytpDKFnMUkAmEpPKV5g9SkNp0hMJngJlyPZW/4k55h8d3XWIArKYZDf0CFdA5i2GQG98XhWK5lBoW3AWWTwGZJUwOm/odeVZEwaVIVu9fRelFT6u/doUUpIP/nJkl/jZAY1T1bd0ku5OIisjZcCvJye5+PXlR3PtWVN4+oMKbvhLKd29zi7TDElHE7iShtYAIN0LqR6VLIrEkt5uqPww+uWK0JchqzOVSAJ1m8wxd5j9CmTYFJDFoppSU/KVc3h4zhecRRZnAUNXmykVjNZQaJv9+L7y6K4jEnyVoY0U8AwuILt/6ReMH53KFSce+jGCGbJWp2fIusjLSj9g8xIAl8vFredP58fnH8GrG2q55sm1dHT3juAqY0BHo9mAn5Q8+Pu4XKZsURkykdhRUwo9HVASCwFZgWn8YzcNSnT1G2HMZM0diwEKyGJR9TooOGZob0QOxg4Y4u1NSnAGWZQzZKPzIDk1fksWh9LQw5Y1wWRkD3IVcmNVM8s/b+R7Z0wm3X3on/WcvoDM6RmyupbOfRp6HMx1Zx3Gry87mhWf7+TbD39Ac0dPhFcXQzqahrZ/zKZZZCKxpdzePxYLAZla3++jbpOaecQIBWSxxt8LdRvCV64Iew2HjrNOgNGeQWZLSjLPcbx1WgwE+gKyEDJkWRNMmWz7zgPe5I/vfYEnLYVvnzppUKd0JycxLjPV8RmyhiEEZABXnzyR++Ydz6bqFq58cBUNDg9IB629aWj7x2zKkInElrKVZoRPNLsh2zx9XYC1jwy622HXdsjT/rFYoIAs1uzcYlrDhqvDIkBqpnljE28li7ESkNlriLfnt6MR/F2hB2RwwEzFtp1t/G1THf982iSy0t2DPm1uVrqjAxLLsqhr6SQ/a2h78s4/uoBHF5xE5e4OLn/gfcqb2iO0whjS0QSZoQRkxeZCQK+zA3eRuODvgcoPYqNcEfbKkCkgo2EzYEHejGivRFBAFntq1pljODNkEJ+zyHwVplQw88Czq0ZMPM4iC7a8D7FkEQ64j+zB97aRmpzE986YPKTT5nrSHJ0ha9nTS2dPYEgZMtsZU8fzv/9yKq2dvXzzgVVsrm2JwApjSEdjaBkyu9OiyhZFoq/2Y9M1OhbKFcFsMQAFZAB1G81RJYsxQQFZrKkphbQsGDslvOf1FsVfGU9zpQmEkmLgxzh7ErQ3QM+eaK8kfOyMXyhNPew3xQPU6dc27+GvpdVcdVIx40cPLVOUl5Xm6D1kAw2FHopji7N57trTSHa5uOrBVawt2xXO5cWOQMDMIQu1ZBGgWQGZSNSVxdD+MYCUVLM3VXvIoH6Teb+ZPbhtAxJZMfBOVvZRUwoTjg1/kGGX1MXToFlfRWjBQiQEZ5HFUdBrfy+hZMhGjYck94BZioeW7SBgwb+cOfSLDrmedBrbuhw7m8seCh1qQAYwNc/D89efxrjRaXz7kQ9YurUhXMuLHZ0+0wktpKYe9p7ZOPq/KOJU5e/D+GngyYv2SvppFplRt8mUKx6k46+MHAVksaS3y/wHCXe5IphMUk877Nkd/nNHSyzMILMFRwvEUdlic6WZ6ZQ+hDlQtqQk80vvSyWLu9q7WfxhBd84ZgLFY0cN+bR5WWkELGhqc2bZop3dyx9GQAZQNGYUz157GlPGj+aaJ9byyseHHjHgKB19mb/hZMhaFJCJRF3TF7G3R8mTrwyZZZmh0LH2b5PAFJDFkvpPINATmYAs3gKGnj2mRNAbKwGZPRw6Tp5f6G95H+rVswGGQz/+fhl7evxcN+uwkE6Z4zGBjFP3kdkBWe4Qm3oMJMeTxl+uPZXjJ43hhr+U8ufVcTQHr6PJHENp6uHOMIGcShZFosuyzO8Au4Q9VtjDoROZrxy6WyFP+8dihQKyWFJTao7h7LBoC7a+j5PGHr4YmUFm8xRAUkr8PL/Qt0cvhHJF25cCsrauXp54v4xzj8xjWl5oQyjzspw9i6y+pYvsUe5BzV0bjKx0N09+72TOOTyXn720iXve/hwrHsqS7aGtoWTIQLPIRGLBnt3QuycGA7ICc0HX3xvtlURP3SZzzFfL+1ihgCyW1KyDjLGRCTK8cbbHyZ6pFit7yJKSzS+deMqQ+SqH9/zaAVlfgLD4gwqa9/TwgxCzY2Da3oNzM2R1LZ3keYZXrvhl6e5kHvjnE5hzXCG/e/MzfvnqZgIO3WMXZGfIQtlDBvHZxEjEaYL7kGMtIMsHK3DQOZlxr34T4ILc6dFeifRJifYCZC816025YiQ2WI4aC+5R8TMrK5ZmkNniaRZZdzvs2TX8DFnvHuj00eXO4uEV2zltyjiOmzgm5FPm9HVlbGhxZkDW0NJJnje8ARmYodm/u+IYske5eXTlDnx7uvnN5TNxJzv0mlv7MDNk3iIzjFZEoseukIjFDBmYfWRZBdFdS7TUb4Jxh5k5tRITHPrbOg51d5ghfYURKFcEE+R5i/szS07nqzQlgp4YejHNnhg/GbLglc1hBLx7zSJ7cV019S1d/ODs0LNjAKkpSYzNTA22j3cakyEb/v6xgSQlufj5RUdy47nTeHFdNdc/9RGdPf6IPFbEdTSZC0ipQ2/8Apg3gF3N0NUa3nWJyODZjXViLiDTcOhgh0WJGQrIYkXdRtPmORINPWzeovjJ4PgqzIt8Unj24oSFt9hccevtjvZKhm84Q6FtHhOQ+X3VPPjeNo4u9HLGV0IsQdtLrifNkRkyf8BiZ2sX+RHIkNlcLheL/mkqv/jGDN7e0sB3Hv2Qls6eiD1exHQ0hZ4dg732zGofmUjUtNSYC6ejc6O9kn3tnSFLRF2tsHsH5Gn/WCxRQBYrgg09IhiQZRfHz76K5hhqeW/LnghY8dFuezgzyGx9GbJNmz+lrKmDH8w6DFcYynFzs9JpcGCGrLGti4A1vBlkgzX/tBL+cNWxfFS+m6seXE1phcPGXQw3IMtS63uRqGuu7mt4FUMXTgEyc8CVlLgZsvpPzTFfHRZjiQKyWFFTCqPz+8u8IsFbbLqXdXdE7jFGiq8iBgOyOBot4KsEV/LwSkI9+Vi42LhlC1NyMvn6jPywLC3PoRkyuzPkSARkAN84tpCHvnMiDS2dzLn/fRY+uZbP6h1SwtfeGKYMmQIykahpqY69ckWA5BTIzE3cDFn9RnNUy/uYooAsVtSsi2x2DPoDGKe/SentMle2Yi4gs2eRxUFZaHOVuTiQPIy+P8luutPHk9JWy3VnHUZSUnia1eRmpbGzrQu/wzoJ1jWHZyj0UJx9eC7v3XI2N547jVXbmvj6H5Zx47PrqdwV4xdlhpsh8xSYK+AqWRSJnpbqyF5kHo5EnkVW/wmke4dXASNhp4AsFnS2QOPnkQ/IvH0ZHKc39miuAqz+7ydWZBWaN4HxkCFrrgzL81vZm02J28elx4bvKmleVjr+gMWudmft1avva9WfF4ah0EMxOi2FRf80lWW3nM2/nDmFVzfUcs7vlnLbK5+wM1bHB3Tsgsxh7DdMTjEVB5pFJhId9lDoWGt5b/MUJG5AVrfJZMci0dFbQqaALBbUbQCsyHVYtMVLGU9zjA2FtiW7TSOLeBgOPdyh0MDasl1s6/IybVQbqSnhe6nJ9ThzOHR9cyfJSS7GjR7ZgMw2JjOVn1wwnff+YxbfPKGIP68u56zfvsvv/rE1thp/9HZBd6sZ1TEc3kLnv9aJOFXHLujthKwYzcJ48hOzZDEQMBkylSvGHAVksaB6nTkWHBvZx/EUmH1BTi+p88XYUOi9ZRc7P0MW8Pdd2RzeL9L7l25jd/J4xvjDO3wzp2+wcsxmdw6gvqWTnNFpJIepdDNUBd4Mbr9sJm/+6GucfUQu97zzBV+7413+tGxbbLTJH+5QaJuGQ4tET7DlfayWLBaYPfXx0BV5KHbvgJ52NfSIQQrIYkFNqSkPG50T2cdJTjFldU7P4PgqTWlgLG4Wjofh0K11EOgdVsC7ubaFd7Y0UFzyFVydzWbQdJjYJX9Oy5DVRWgodKim5IzmvnnH8+q/ncHMomx+9foWZv12KYs/rKDXH4jewoY7FNqWVWhKFi1n7TUUiQv2UOiYLVnsazLVVh/ddYy0+k/MURmymKOALBbUlEZ+/5gtu9j5AYOvwpQGJrujvZL9eYvNm0B/b7RXErpgy/vQA7I/Lt1GZmoyx8040nyiJXylITl9JYsNDsuQNbR0RWwo9HAcVejlye+dzF8WnsqE7HRufXEj5961jFc31BCIRuMUO0M2nD1kYDJkvZ2mdEpERlZzjA6FtgVnkSXYPrL6TeaCdu70aK9EvkQBWbR17DIpAAdJsAAAIABJREFU5JEKyOKhjCcWZ5DZsieaAd+tNdFeSeiCQ6FDC8jKm9p5dUMN3zp1EqPG9/07hbG5QlpKMmNGuR2ZIYvkUOjhOnXKOF64/nQemn8iqclJ/Ov/lnLxvStYurUBaySzTMGSxTBkyECzyESioaXaDIXOjLGh0DY7Q5Zo+8jqNsG4r4A7I9orkS9RQBZttevNccQCsjjI4PgqYnP/GMTHLLJgQBbalc0Hl20nJSmJ758xuX//QEt4A9RcT7qjMmSdPX6a9/SM2AyyULlcLs49Mo/XbziTu646huY9PSx4bA1X/2k1H5WP0HDpcO4hA+dfgBJxopYaU8mSFKNvMxM2Q7ZR5YoxKkb/pySQmlJznBDhhh627OK+DI5Drwr5e80LfcxmyCaZo5PLQpurID0b0jxDvmtDSyfPr63i8hOKTPBh/9ILc/vx3Kw0GhyUIRvpodDDlZzkYs5xRbxz0yx+8Y0ZbNvZzuV/fJ9rnljL1roID5dubwRckJE9vPMEAzK1vpfh6ezx80lNc7SX4SzN1bG7fwxMBj4pxbnvhULR2WwuFquhR0xSQBZt1etg7BTIGDMyjxecRebQgKGl2gSUsTaDzGa/CXRyhsxXGXIG8pEVO+gNBLjurCnmE6mjzM92mH/pOS1DZg+FHukZZMOVmpLE/NNKWHbLLP7j64fzwY4mzvufZfzomfVUNEVouHRHk2l5n5Q8vPOMGg/JqSpZlGG7950vuPDuFXz/8TWUN4WvQVFca6mO3f1jYDJ3oxNsOHT9p+aoDFlMUkAWbTXrR65cEfoDGadmcGJ1BpktJc28yDt5+HZzVUgBb3NHD0+tLufCmROYNC6z/wueCWEvWczLSmNna1d0mk6EwB4Kne+QDNmXjUpN4Ydnf4Xlt5zNwq9N4fWNtfzT75fyXy9vCv/4gY7G4e8fA/OGK2uCMmQybO9saaDAm87q7U2ce9cyfv+PrezpjoEREbHKHgodqy3vbYk2i6x+kzkqIItJCsiiqa3BXL2dEOGB0HsLlvE4NCALziCL0YAM+lrfOzkgqwwpIHtiVRnt3X6uP+uwfb+QNSH8JYueNHoDFrs6nDFDpr4vQ5br0IDMlj0qlVvPn857/3E2V5xYzFMfVPC1O97lzje20rwnTMOlO3aFJyADM5RWe8hkGHa2dvFpbQv/fNok3rl5Fucflc/d73zB7N+/x9831Y5swxunaG8Ef9ewZ1lGnCfBMmR1G03FSqwHyglKAVk0BfePjWCGLHWUKeVxekAWyy/0Th4t0NkMXS1Dfn47unt5bOUOzj48hyMnZO37xawJYW17D/17sZzSabG+pZMMdzJZ6SnRXkpY5HvT+dWco3n7xrM498g87n3XDJfeVB2GfTYdTeELyLxFYb8YIIllxRdmsP3XpuaQl5XO/1x9HM8sPBVPegrXPbWO+Y9+yLadbVFeZYyx/8/F+ht/T0HiZcjyjgKXK9orkQEoIIummlLABQUzR/ZxnRww+CpNSWBKDO/FyZ5orsoHHFjSEpxBNrSA7C8fVrK7o4cfnP2V/b+YVQjtDdAbvmxWbpazZpHVtXSSl5WGK85+EZaMz+Tuucfx2qIzSEly8ds3tg7/pO1hKlkE01SgpcaZ/xclJiz7rJFxmakcWdB/oemUKeN49d/O4L8uPpL1FT7O+8Mybv/bZtq7HNy9OJyCAVkM7yEDkyHr9EHPnmivJPICfmjYDPlHR3slcgAKyKKpphRyDg+pm92weIscnCErj+1yRTDlfoEeZ5ZC+Ia+R6+7N8BDy7dzUskYTioZu/8Nsuz2wuG7EpnrMRkyp3RabGjpckyHxVDMmODl+2dO5r3PdvJxpS/0E1mWyZANdyi0LavQNAFqqw/P+SShBAIWyz9v5Iyp40lK2vdiSkpyEt/96mTeuXkW3zi2kAff2845v1vKKx/XqIzR3jMcy5UskFit73ftgJ4OyJsR7ZXIASggixbLMh0WR7Jc0ebty+A48ZdGc+gdAEeM3freiUFvcAbZ4H+RvrS+mtrmTn4wa4DsGPSXrYQxIMvx9GXIWpyUIYvfgAxg/mkleDPc3PPOF6GfpNNnAqhwliyC9pFJSLbUtdLY1sWZU3MOeJscTxp3XnEML1x/OjmeNBYtLmXuQ6sjPx4iljVXQZJ7+LMEIy04HDoBArL6jeaohh4xSwFZtLTUmDKuaARk2cXmSknHrpF/7OEI+M0LfaxnyJw8HLq50rQKz8wd1M39AYsH3tvG9IIsZh1+gDctdtlKGPfypLuTyR7lpr419jNklmVR39JJvje+A7LRaSl876uTeWtzPZ/WtIR2Evs1KVxv5BSQyTAs+9zeP3bon8cTJo3h5R+ewX/POYotda1ccPdyfrHkU1o6w9TsxknsDouxOhTa5gl/9UbMqtsErmTIOSLaK5EDiPH/LXGsZp05jmSHRVtwFpnDAobWOgj0xn5A5nVyQFZlAqhB/iL9xyd1bN/Zzg9mHXbg/VHB4dDhbX2f60lzRIaseU8PXb0Bcj0xvO8xTBZ8tQRPWgr3vvt5aCdobzTHsHVZDP/FAEkcyz/fyRH5nkF3R01OcvGtUybx7k2zuOqkYh57fwfn3PkeL3xU5ZgRHWER6zPIbAmVIfsExk8Dd3xfGHQyBWTRUlNqrlZEY2J6cHixw0rqgh0WYzwgsztZOjUgG2S5omVZ3L90GyXjRnHB0QUHvmG6F9yZEem06ISmHvV9QWO8Z8gAvBluvnN6CX/bVMfn9SGUbHU0mWNmmAKydC+kjtYsMhmyju5e1uzYzdemHbhc8UDGZKbyqzlH8/IPv0rRmAxueu5jrnhwVXi6kDpBc5VpqBPrMsZAclpiZMjqN2n/WIxTQBYtNaWQeyS4M0b+se0Mk9PKeMI8FDoQsKjc1cG7WxvYVN1MZ08YO7FlT3TmHjJf5aCf3w937GJjdTPXnnUYyUkH6R7ockVkFlmOJ80RTT3q+tbo1KHQQ/W9MyaT4U7m3ndD2EvWEeYMmctlrtS3OOy1TqLugx276PYHOHMQ5YoHMrMomxevP507vjmTssZ2Lrl3BT99aSM+h8xPDEkgYAKcWG95D+b1IRFmke3Zbd6PRCMBIIMWH0NxnMayTEA2/eLoPH7GGJOxcFrA4Cs3xxA6N+1u72ZLXStb61rYWt/KlrpWPqtrpb27PwhLcpk23kfkezg8L4sjCjwcke+heMyo/TpsHVJ2sSkRcBJ/j/lFOsjnd235bgAunHmQ7JgtqyDsJYt5WensbOsiELCG/u8zguxZafHe1MM2NjOVfz51Eg8t386/z57G5PGZg7+znSELV0AGfV1lFZDJ0Cz/rJG0lKSBO8cOQVKSiytPLObrR+Zz11uf8eSqMl7bUMst5x3BVScWx/RrV0g6GsHfbYayO0EizCKz34vkqeV9LFNAFg27y8wVi2g09ABzVSi72Hkldb5KyMwxJYEH0Nnj54uGNrbWtQYDry21LfuUtmWPcnN4nodvnlDEEQVZHJYzmp2tXWyta2FLXSuf1LTwt011wSaUo1KTmZrn4Yg8D4fnmyDt8HwP40YfZE9Q9kT47A0TfDtl9lRLNWD174E7hM/qWynMziAr3X3oG2cVwo7lw1vfl+R60ujxW+zu6D74v0WU1TebgMyenZYIrjlzCk+sKuP+d7/gt1ccM/g7tjdCSgakDiGIOxRvIdRtDN/5JCEs+3wnp0wZR7o7OSzn845yc9slM7jyxGJue+UTbn1xI3/5sIL/+42jOLY4OyyPERPsSggnlCyCyZA57eLpUNVtMkdlyGKaArJoqCk1x2gFZODMWWS+imCwEAhYVO3ew5a+IGprXStb6looa+rA37d5OjUliam5ozlj6vi+ICrLbND2DDygd+9MT0d3L5/VtwWDtK11rby5uZ5n1vY/ZzmetL5smh2oZTE1b7T5Be6dCL2d0NYAnrwIPzFhMsSh0FvrWpmWN3pw586aAG11plNmUnje4NgZp4bWrtgOyFo7GTPKTVpKeL5vJ8jxpDH35In8eVU5i/5pKsVjD3wRZR8du8KbHQNzpb69AXq7YnugvMSMGt8evmho4+qTwj9i5cgJWTxz7am8vL6G/359M5fet5L/n703j27jvs+9n8FOgli4AaS4iCLFTbY2W4ttLdZmKfGSvXaWJk2bpElau6f3Nr3v0r5973nv7XLbNCfXbpq6SZrWSZwmcZvYcSzJlmRJtK3VkqyVALiJm7BxwUIQ+7x//DAQKILEAJjBzIDzOccHNgUMfqaAmfn+vs/3eZ7Z0oL/9qFuUZ/HWMPMa0pBsgiQgmzwhNCr4BfXdXJerZLIvcgKRS7IhGDyErEWtwg4YGlquVsYipzpuSj6nX7c5xzCbXU7/uI778LuCiCUITdsralEd4MBj69vRE+DEd0NBrTVVkKlLGxMslKjwqYW84KdS5qm4QlGSPfNGUgXaj86exuReBJASvZYq8enDFH8AYAzl66g8b6daK0pQPZYatIFWe6bkFgiiSHPHB5dyur+XoyriEPmnOeus1WRMK6FLn8YvY1GTo7JB05feYdCL8VXd3fgJ2dH8d1Tg/irj7OUyoSmuDP0YGB26v2TQM0abo8tU5b0MXb3BRh6sIGiKHxscxP291rw/HEHfvjuCA5fv4NvHOrGZ7e1FnzdEgWMNF0yksUGIOIHIkFAy3KDUWq4rpP8MamodVYockEmBJNXyJdDpRFuDeYWcvMTneNWHsQRTl8Yf/6ra7g67oM7EAGFJPq1k7ii2IiKRiWe3tKSlg52WQ3Qa/n/KFMUBYtBB4tBtyAoNJGkcXtqbkGRdmGS/E5/crQPrx+Oo0KtRJe1Cr+/u4PdzJUQMK6bLKQmt6fmEE0k0W01sDu2IbVb6p/grCDL7JCJGXeg/EOhs9Fg0uG3tjTjFxfH8dy+tWg0sTAwCnm575BlZpHJBZkMC047vLAatei08HuDbtCp8WdPrMPTW1rw/752A3/x6g38+/kxvPyV7TBXCnh/UAz+cbLhzPX3mC+YWJagqzwLskQccN8Ctn5Z6JXI5EAuyEpNMkkKsg1PC7sOU4bTYn23sGvJwt8e6Uefw4snN6xCT4MB95vC0P4yhs9/aBe+sP0hoZe3AKWCQnt9Fdrrq/Bhxv493An8zR/j/95Rhd2WDeh3BvDrq5P44bvD4i3IfKkZPRbOnzZnEADQxbYgY+Qr/jsAR6MF9akOmdidFp2+MHobxNvB45Ov7+nAzy6M4cVTQ/jvH2GhCAhNATUd3C6C2amXs8hkWJBI0njH4cVj66xLZytyTKfVgJ98eTtevTKJP/7ZFbz2wSS+8HBbSd6bc3wT0giFZkhnkd0Bajk+94iB6UEyPmGV58fEjkS+MWXE1AAQDQBNAgRCZyLiLDK7K4BfXpnAF3e04e+f3oiv7G7HwzVzAABK7KHQDDojoDNjFe3G01tb8BdPrcOH7muAzRkATYs0INQ3xtrQw+YKQEEBa9nuIBszZGMcoVMrYapQi7pDFk8k4Q1GYF1Bhh6ZNFdX4hMPNOGn50fhDrAonOemeJghS20GrHSnRZomw/1iPf+IhGsTPvjmY7zJFZeCkTGuqdPj2C13Sd+bU/yT0pErAnc7ZOVqfe+SDT2kglyQlRoxGHoARLIIAD7xOS1+6007qjQqfG13xm4Vs06pFGTAoiyynkYDApE4JmbnBVzUMuQRCm13BtBWq2fvQFZZCyjUnHcpLAZt2lZejHiDUSRpwLoCQqGX4g/2rEUskcT3Tg8t/8R4hGxWcT1DpqkEKmrkDtmp/wX80w7AfkTolYiaPrsHFAXsXFt4/lgxHOi14OzgFIKRuCDvXzT+cekYegALO2TliPM6oFABdV1Cr0QmB3JBVmomLxNb5zqBZYKGRvIlFdmu8dXxWRy54cSXd7WjWp+hoWcs+s3cu17xhrl1QbRATwOR9/XfCQi1oqWh6VRBxt7ynrVcESDyFSP3eS8Wo1bUHbJ0Bplh5RZkbXV6fHRTE358dhRTwWX+rvjIIGNY6Vlk5/4ZOPnX5N9vvyvsWkTOaYcH65tMqNELM8O1v9eKaCKJPrtHkPcvimSSyNKlYnkPAFojoK4s7w5ZXbfsMCsBli3IKIpSURQ1SlHUydQ/6ymKupLx34+VaqFlw+QloHEjoBR4fE+hJLtYIpMsfvNNO2r0Gnxp1z3D97OjJNBam0cRIDTmVvL7TUmEmALG5hJhQRaaBmIhVgVvOJbAyNQcuhry/LswNnEfDm3Qwe0Xb0HmTBVkDSu4QwYAf7h3LcLxBH7wzvDST0oXZDx0JkzNd+24VxpXfwEc/lOg+wmgaQswdl7oFYmWQDiGS6Oz2NUpTHcMALasroapQi1N2eKcB0jG7krUpQBFkS5ZOXfIZLmiJMjVIdsA4Kc0Te+haXoPgEkA/cx/0zT9Fu8rLCcSceDOVeHligymFlFlkZ0bmsJpuwdff7QDVfe6Js6yn28SDeZWIDZHih0QR63m6grcuuMXeGFZYD4HLCSLA+4gkjTYOywyGBo5l43VG7VwB8KinctjOmQrKRQ6G2stVXh8fSNeOnMbs6Fo9ifNeckjHx0yYxORUq00HG8Bv/oasHon8Kl/AVY/TFQacfFuYgjJe4NTSCTpBS66pUalVGBvdz3etrnTmZqSgfmOSakgA8i1qRw7ZKFpIDApG3pIhFwF2UMAnqQo6jxFUT8AsAPANoqi3qMo6lcURUmoXSECvDYgPi+ugkwkHTKapvHNN22wGrX4/MOrFz9hdlRa82PA3QLSlylbNKLfKcIOWbogy1302lMdvu6GPC2CjatIh4zD4slq0CGWoDETinF2TC5x+cNQKijU6Vd2QQYAz+1bi2Akjh++O5L9CbxKFpuAsA+IiPC7xxejZ4GffR6w3gd85qeAWge0bAcSUeDOB0KvTpT0OTzQa5R4oLVa0HXs77Viei6Ky6Mzgq4jb9IZZBKaIQPKt0PGGHpYBcy8lWFNroLsAoADNE1vA6AG0AbgEE3TjwC4CuB3s72IoqjfpyjqIkVRFz0eCeqg+WLiEnkU2mGRwdxCdk8Swg8Pn7R7cGFkBs/t61xsFEHTpGCQWkHGrPeeObJh7xzCscQSLxKIPEKhba4ANEoFVtfmmV9nbCL2u/Pc3WQwnSdWDn4C4PRFYDFoxR8KXgJ6Gow4uM6KH747jEA4SwGd6iRDz4dkkdkcWSGyRed14OWnSSH6uf8grq8A0LyNPI6dE25tIqbP4cXDHbXQqIQdr3+0ux4qBYW3brkEXUfeMN8vluZQooHpkIlUaVEwTsZhcb2w65BhRa6zzlWappltg4sAKgAMZPx3Z7YX0TT9zzRNb6Fpekt9vXCtf9ExeRnQGLjP2SkUUwtAJ0lRJiDJJI1vHrWhtaYST2/JUhCEplLzTVIryFL/L5kFWaMBiSSNAXdQoEUtgW+cmM1U1uR8qt0ZQHu9Hmplnjct6Swy7j5vTOCyS6RzZCs1FHopntvXCX84jpfO3F78hyEvAIrMinJNOnZhBcgWp4eBH38CUOuBz/8SqMq4BhusQHWbXJBl4fbUHG5PhUpud58No06N7e01OC61OTL/BKDUSicUmsHQQO4xIiIcJygG13VAbwGqLEKvRIYFue6ofkRR1EaKopQAPgbg0wCeSv3ZpwDIuod8mLwMrNoknsBEkWSRHbnhxI1JP/74QGf2nclZCVreA4DOTBycMn6/jNOiTWyyxdlRUkCyCEK1u4LoztfQA+ClILOIPBza6Quv2AyybKxvNmFvdz2+3zeEUPSeznxoihRjCpZRCvnAuL6Ve4cs4AJ+9DEiS/z8L7OfM1u2E2OPcusGFMlpB5lhFHJ+LJMDvVYMuIMY8c4JvRT2+FOh0CUK1OaMcs0ic16TDT0kRK7K4P8D8CMAVwCcAfA4gD+jKOo6gAiAf+N3eWVEPEp2K8QyPwbcvVgLaOyRSNL4+zdt6LRU4aOblhgEZgoyqZl6UFRqTu9uh6ytVg+NSoF+p8h24lhmkAXCMUzMzudnec/AFGQcdmQtKTt5sVrfu/xhNMgdsgU8u68TM6EYfnL2ngzEOS9/O+uGRgBUeWeRzc+SzljQA3zuFcDSk/15LduAoAuYzdKlXMGctnvQXF2BttpKoZcCgBRkAHBMSrJF/6T05IpAeWaRJeKAp1829JAQyxZkNE1fp2l6A03T62ma/jOapu/QNL2dpun7aZr+Ck3T4pykFyPuG2TXUkwFGXPiFLAg++XlCQx65vAnB7ugXGrOhlmf1DpkwKJwaJVSgS5rlfiMPVhmkNldRGqZt8MiAFRZAUrBaYesQqOEQacSZYdsPpqAPxyHRS7IFvDg6mrsWFuLF08PLZylDE3xMz8GAEo1uekq1yyyaAj46acBjw349I+B5i1LP7dlO3mU7e/TxBJJnBmcwu6uelAi6e601FSi22qQVkHmm5CeoQdQnh2yKQe555QLMskgEu3cCmDyMnkUU0GmrgD09YJJFqPxJL59zI71TSYcuq9h6SfOjhLpX4W5dIvjCvPCDhkAdFtF5rQYCwNz7jwdFgsoyJRqomfnuEthNepEOUPGWN7LHbLFPLevE95gBP9+PuO7EZrid/akXMOhEzHgF18kroqf/B7QsW/551vWAZoqeY4sg8ujswhG4tgtYP5YNvb3WnBhZAY+kbrILiCZIOoHqVneA2SzECivDlna0EMuyKSCXJCViolLZD6iuk3olSxEwCyyn10YxfjMPL5xqHv5XclZCTosMphbyaDw/Gz6R72NBngCEUwFRVJE+Nk7Y9mcAVRqlGgyVxT2XsZVgJ/bi57FoBWlyyITCi2beizmofZabGurwT+dGkIknuqS8V2QGZvKT7KYTAK/+gPAcRR48lvAfR/P/RqFknTQ5IIsTZ/DA6WCwsMd4irIDqyzIpGkcdIuAXOPOQ+QjN+d15QS2iqy6VtOHTLXNUCpAeq6hF6JDEvkgqxUTF4h3TGRyCHSmJoF6ZDNRxN4/sQAtq2pyb0rOTsqvfkxBtNip8VusRl7pE1T2HXIOq2Gwm3cmSwyDhF9h8wkm3pk47n9a+H0h/HK++PEYKIkHbKJ8jGzoGngyP8JXPs5sO//Abb8HvvXtmwHXDdWVi7bMpx2eLGpxQxThVropSxgU7MZdVUaHJOC2yJjmCPFDhlQfllkzutAfTdRpshIArkgKwWxecB9U1xyRQZzK5HxlPgm5aUzI/AEIvjTXN0xqWaQMWQxTulpIJlAt8RSkKUzyHJ3yOyuALqteQZCZ8JDQWYxaOEJRECL7EabKcjkGbLs7Fxbh00tZnz35CBioVmyu853hyw+z2kOnqCc/jvg/IvAw88Cu/4kv9e2bCORJxPv87M2CTEzF8XV8VnsEplcEQAUCgp7uy04aXMjlkgKvZzl8ZdDQVZOHbIb8vyYxJALslLgvAbQCWCVSAKhMzG1kJuU0FTJ3tIfjuG7pwaxp7seW9ty5F6FZ4nkj0X3RpRkCYeuN2hRq9fAJhanRd84ACrnhdQbjMAbjBbmsMhgXAVEfECEuxw2i1GHaCIJ37y45ixc/ggqNUoYtCqhlyJKKIrCH+1fi/GZebx14Qb5IV+mHoAoTIw44/z3gLf/Etj4WeCx/5G/8qJpCwBKNvYA8O6gFzQNUeSPZePAOisC4TguDE8LvZTlkXxB1lg+HbI5LxB0ygWZxJALslIgRkMPhizhxXzzg75hzIZi+MbB7txPnpWwwyJAdvzVlYtkoT2NBvEYe/jGyMUoh7ShKEMPBuZizeGFj8kiE5ts0ZmyvBeLa5sY2dttwf1NRrx+9hr5Aa+SxTLJIrv2CvDGnwLdjwMfeaGwXMsKM2DplefIQOzujToVNjSZhF5KVnZ11kGjUohftugbB1Q6oDLHJqtYYTpkIlNaFIQzdT6VDT0khVyQlYLJy8RdTox2sCXeNZ6ei+L7fUN4fH0D7mdzAZRqBhlDOotsYeZPT4MRdlcAiaQITv6+MXZyxVQBWZDlPUM6HJq7m2LGNENsxh5ufxgWORR6WSiKwrN7OxHxe8gPeJUspj7jUjb2cBwDfvlVYPUjwKf+BVAW0X1t2QaMXSDGICsUmqbR5/BiZ2cdVEpx3g5ValTY0VGLY7dcopNlL8A/Kc1QaAZDI7GJLwdJsyvlsCh3yCSFOM9A5cbEJaDpAXGeqNKmE6UpyP7p1CDmYwn818dYOv+kM8hW87covrkniwwgXaZwLInbU3MCLSqD2TFWklCbKwhzpRr1hiKKDCbvhcM5MrF3yGSW5+A6K9aZiNw0WcHj7rq+HlCopWt9P3Ye+PnnSWfrMz8lsSXF0LKdyIe9Nm7WJ0EGPUHc8YWxq1OcckWG/b1WjE6HMODmTurNOf4J6coVgfIKh3bdAKoa+JWAy3COXJDxTSQAeO3ilCsCxIpfU1WSmxSnL4x/e28EH9/cjLUWll2W2VEi+ZOqDALImkXWmzL2ENxpMZkkF1KWhh5dVkNxErx0h4zDgizVhRJTh4ymabj8EdnyngUKBYUPtxO57JsjiRzPLuqNiGxRigWZ6ybwk98iN42//Z+AjgN5XTogeuXKFk/ZvQAgSkOPTPb3WgAAb4k5JNo/yeo6IlrS4dBlUJA5r8tyRQkiF2R8c+cqAFq8BRkjqSuBZPGFEw4kaRp/fKCT/YtmR0mHSYzdRbaYW4kMIsNiutNaBQUlAqfFOQ+RaeSQhNI0DbszgJ5i5scAsqtfUcNpQVapUcGgVcEtog7ZbCiGaDwpF2Qs6TFGEYEG3z41jiSfMl5js/QkizMjwI8+Tr47n/8VUGXh5rg17UQiuoKNPfocHrTX69FcXSn0Upal0VSB+5uMOC7WObJk4q5kUaqkO2QSd1qMRwFPvyxXlCByQcY3k5fIo1gLMiCVRcavqcfoVAg/uzCGT29tRUtNHhc/KWeQMWSRherUSrTV6YV3WmQK8Ry/4zu+MAKReHEOiwx8WN9NnAwAAAAgAElEQVQbxRUO7QrIodD5oJifRqKiBv2uII7383jTaWqSlqlH0A289DEgHiadsWoOpdsURbpkK7RDFo4lcHZoCrtFLldkONBrxaXRGXiD4tl4ShN0EydpKUsWq8pEsui1A8kY0LBe6JXI5IlckPHN5GWyK8vVriYfmPnvkH37mB0qJYXn9q3N74VMh0zKMPNv9/yOexpE4LSYLsiWl5rYuHBYZDCuAgJcZ5GJKxza6ZNDofNizosKkwWtNZV44YSDP/MCYxP57CV5lEZyxfws8KNPAEEX8LlXAOs67t+jZRswNQDMlS72RCy8f3sG4VgSu7vELVdkONBrBU0Db/O5YVEoUre8BwC1joxwSL1D5kpFiMgdMskhF2R8M3kZWLVJ6FUsj6klJanjZ2DY7grgl1cm8DsPt+UXkhv2kxwyqWaQMWTJIgOI0+LtqRDmInEBFpUiHSuw/O+YcVjsYjv7txw8dMisYuuQMaHQBrlDxorQFCh9Hf5gTweujvtwyu7h531MzSSAOijiWRwAiM0DP/0MkR498yOgZSs/78PMkY2vPNniabsHaiWF7Wt4dPbkkPtWGdFg1OGYGOfImLlMk4QLMiCVRSb1guwaoNQCtXlufssIjlyQ8UloGpgeIg6LYoYpGHgadv/Wm3boNSp87dGO/F7ok3gGGYO+npwg77G+Z7pNTL6XIPjGAa0xp0mAzRVAg1EHU+XyWWWsMDaR2bU4dx0ti5F0yMRiC81062Tbe5aEvEBlLT7xQDOazBV44cQAP3+X6ZgPEcsWEzHgF78LjJ4BPvEisPYAJ4f1h2P4i1evYypT8rZqM6BQrUjZ4mmHF1tW10AvkeB2iqKwv9eCPocX4ZjIOrzMBpuUO2RAKotM4pJF53XA0lNcJIaMIMgFGZ+MXyCPzduEXUcueMwiuzo+iyM3nPjyrjWo1mvye/FsGVjeA8TdzdyyKFqAcVoUVLboG2c1o2d3BdDFhVwR4MXNymLQIhpPwj8vYLcxA6c/jBq9BlqVUuilSIPQNFBZC41Kga892o73b8/gzCAPMjrmhtEvUqfFZBJ49VnAfhh44pvA/Z/k7NDf7xvGS2du48iNjA6AugJo3LjijD3cgTBu3fFjl0TkigwH1lkRipLZN1HhnwBUFUTyJ2XKokN2HbDK82NSRC7I+GTsPEApxd8hS5tOcG/s8c037aiuVONLO9fk/2Kph0JnYlpsfd9cXQG9Rims9b1vNOf8WCJJw+EKottaxc17pq3vOSzIUlJYl0hki25/WDb0YEs8AkT8QCW5Of6tLS2wGLR4/oSD+/diJFVi7JDRNPDmnwFX/x3Y++fA1i9zdmh/OIYfvjsMALg8OrvwD1u2AxPvk87cCuEdB7G7l4qhB8PD7bWo1CjFJ1v0T5DvlpTdkIFUh8wp3bD0gIuoT2TLe0kiF2R8MnaOfDE0eqFXsjyGBiJb4ViyeG5oCqftHnx9TwcMugKkbr5RQKUTtyEKW7KEQysUFLoaDLh1R0CnRd94zoJsdDqESDzJjcMikNGl4O6mmAmHFov1vdMfhlWWK7IjNE0eU1mDOrUSX320A2eHpnFhZJrb99KZS5a7mDd93wTO/iOw/evA7m9weuiX3htBIBzHmjo9rozdW5BtIy6OzqucvqeY6XN4UavXYF2jUeil5IVOrcTOtXU4fsstGnk2ALLBIWXLewZDI3GLDHmFXklhuK6TR+t9wq5DpiDkgowvEnFg4tLdoWkxo1CSm2QOJYs0TeObb9pgNWrxhYfbCjvIbKp7I/VdN4BIFuc8QDS04Mc9DUbYXAFhLq6RIDFzyWHowXTwOHFYBABjSrLIobEH041izDSExuWPoEHukLEjlJJf6e/Kxz67rRV1VRo8f5zjLhlFkXOd2CSLF34AnPifwIZngEN/xek5by4Sxw/eGca+Hgs+sbkJA+4gfPMZ3TBGUr9CZIvJJI0+hwc7O+ugUEjv2nJgnRV3fGHcmBQ4MiUT/yRxk5Y6Bolb36cLMrlDJkXkgowv3DeA2Jz458cYTItnnIrhlN2DCyMzeG5fJ3TqAudoZsekb+jBkLa+X3gj2NNgwGwoJoxle9oZK4fDoisAigLWWjiSLGqNpEvB8QwZALgDwnfIYokkvMFIfo6iKxlmN7ryrttdhUaJL+9qR5/Du7ijUyxiyyIbOgn85k+Arg8BH/0OmTnlkB+fvY2ZUAzP7VuLza1kxufqeMbv1NREzgFSNPZ47wXg9N/l9ZJbTj+8wajk5IoM+3osoCiIJyQ6mSDncoE7ZJOz83jbVuTvJD3fLNE5Mud1suGUUhvISAu5IOMLZrexRSIFGYdZZMkkjb87akNLTQWe3lLE/Fc5hEIzLDGn15PqOvULERDNsiCzuQJoralEpYYj1yaKSlnfc3dTrNeqUKVViaJD5g1GQNOQO2RsYTpklQsNFn77odUwV6rxAtddMmMTp5+9orn0EukOfuqHgJIDF9MM5qMJfK9vCLs667C5tRobWkygKODKojmybdLrkCXiQN/fA+98Oy/H1tN2sgGwq1Nahh4MdVVabG4xi2eOLOAkMj+BLe//7qgNX/m3i4jGi5j/SnfIJFqQua7L3TEJIxdkfDF2niS/S6XDY2ohu1wcDHYfueHEjUk//suBLmhUBX7EoiGycy6V318u0tECi7PIAIGcFpm15JghszsD3M2PMRgaOc8isxi08IigQ8aEQsszZCxhQokrF+ZBVWlV+NKONTje78b1CR9372dqITlkHMYuFEwiBjiOAZ2HAE0l54f/6flReINRPLevEwBg1KnRUV+VZY5sOylSxThbtxTj54nkOhokEQEs6XN40NNgkHQHe3+vFdcmfOlzjaCkLe+FkywmkzRO2T2IJ2mMTs8VfqAqK3mUYkEWjwBeu2zoIWHkgowvxs6RME+pzD+ZWwA6WfRNciJJ4+/ftKHTUoWPbipix6xcMsgYGOOUezpkpko1Gk069Ath7OEbJ2tidgWzEIknMOydQzfXBZmxiVOXRYBkfomhQ8bIT2WXRZaEpgBQWS2zf2dHGww6Ff7hxAB378fs5HO8IVAQo2eAiA/o/hDnhw7HEnjx9CC2r6nBtjV3JUybW8y4PDa7cG6VUXJISbZoOwwo1CTj0f4mq5eEonFcHJnB7i5pyhUZHltHCofj/SLokjHzmAJKFq9O+DA9FwUADHqKKMiUapIbKsUZMo+NhN7Lhh6SRS7I+CDgIiHAUjD0YOAoi+yXlycw6JnDnxzsgrKYgenpIfJYLgWZQkl+x8z/VwY9DQZhOmSzY+Qiqlh6xm/YO4d4kuYug4zBuIpc9JLcBZxaDDpRzJAxRaFckLEk5AUqzFmDTI06Nb74SBuO3HByFw/Bg8tnwdiPAkoN0L6X80O/8v44XP4I/mh/54Kfb2o1Y3ouirHp+bs/tN4PqCulJVu0HwXadgBtOwHHUVYvOTc0jWgiKV65ovsW8M0uYGpw2ad1WqrQUlMhjjkyZmNDQMni2/3u9N73UDEFGXDX+l5qpA095AwyqSIXZHwwnrqoScXQAwBMqcKnCGOPaDyJbx+zY32TCYfuW7rrwgr7UUCtJ6Gl5ULrI2SA/x5ZaHeDEYOeIGKJEmefsAiFTjssct4hW0XmDoLc3VBYUx0yoe2gXf4wVAoKtfkGoa9UQlOL5scy+b0da6DXKPGdtznqkqU3n0RQkNkOA227AC1HhjkpYokkvntyEJtbzXikY6EUdFOLGQBweWzm7g+VaqDpQel0yKaHAK8N6Pow0HUImBrIWcQAwGmHB1qVAlvbRGp6cO0XRE47enbZp1EUhQO9Vrwz4EUoGi/R4pbAN0GKeZ1ZsCWctHuwqcWMeoMWQ55gcQczNEqzQ+a8TsK5azuEXolMgcgFGR+MnSO7nlIqJtI3KYXPEPzswijGZ+bxjUPdoIqRaiYTQP/rQOdjgLqi8OOIjd4ngbAPuP3uwh83GhBL0MXv7OULi4LM7gpApaCwpo7jLD1G3hLgTjZmMegQiSfhDwt7g+L0h2ExaCVpqS0Ic95F82OZVOs1+O2HV+P1q5PF32wBdztkHMZ8FITXAUwPAt0f5vzQv7w0gYnZefzRvs5F5+JuqwEVauXigOjmrcCdq0C0xOehQrAdIY9dh8h1AgAcb+V82Wm7B9vbawt3/uUb22Hy6LXlfOqBXiui8WQ65Fow/OPkOyXQeIY3GMHV8Vns7bagvU6PIe9K7ZBdAyy9yypeZMSNXJDxwdgFoHEToJaQZEmtA/SWRaYTbJmPJvDCiQFsa6vB7mLlIKNnSWbXuo8Wdxyx0b6X7GD1/2bBj7uFcFpMxIlkK4ehh80ZRHu9vnBzlqVgCjIO53gsRiYcWtg5Mrc/AqtJQt99oQlNL1uQAcBXdrVDo1LgO2/n7oLkRFMJVNQIL1lkbr67DnF62Hgiie+cHMD6JhP2dC+elVIpFVjfbMpu7EEngMnLnK6HF+yHgfoeoGYNUNMO1HbmlC1OzM5j0DNX/PWJL6aHAfdN8u/e3M6i29bUwKBTCS9b9E8KOj922u4BTYMUZPVV3HTI5tzkGikVaJp0yOT5MUkjF2RcE4+SC5pU7O4zMTUXLFl86cwI3IFI8d0xALj5KqDSAZ0HizuO2NBUAmv3k4IsQ1bXXlcFtZIq7RxZkLEqzuGw6OLBYRHImOPhtkMGCJ9F5vSHZcv7fAh5Af3yBVldlRaf3bYav7oygdGp0LLPZYUYssjsR8jsFsdzsr++OonbUyE8u2/tkufizS1m3Jz0IxLPmOFs3koexS5bDPuA2++R3DaGrkPAyDsk7H4J3nF4AEC8hh72VNevYQMxaMiBWqnAo131ON7vRjIpoEzbl3tjj09O2jyoq9LgvlVGdNTrMROKYSZl8FEQhgZicDbn4W6RfBNwAvPTQIM8PyZl5IKMa5xXgUREmgVZgVlkgXAM3z01iEe76he4eRVEMgnc+jXQsZ/zuQpR0PMk2ZnP2IXWqBToqK8qrdMiU3ibl5YshqJxjE6HuJ8fA0hHRKnhtEvB2My7A8J2yFz+sGzowRaaTs2QLV+QAcBXH22HUkHhu6c4mCUzNgvbIQtNEyVAF7fuiokkjX84MYCeBgMe67Uu+bzNrWZEE0ncnMw45+hrSadp7AKna+KcgWPETS5T6tl5EEhEgeFTS77stN2LBqMOnVwF3HON7Q2gvpcUlzMjrGIZHltnhTcYwQfjHIensyURJ5t7RmEMPRIpu/tHuyxQKCi01xNp/ZC3iC5ZFZNFJqE5srShh2x5L2XkgoxrmN1FKRl6MJhayFxRnqYI3+8bxmwohm8c7C5+DRPvk7midR8p/lhipOsQQCkXyRZ7GgzcucixgUUotMNFLmqcOywCZN7A0Mip9T2TK8TYzgtBKBpHIByXCzK2RPzk5noZUw8Gq1GHZ7a04JX3xzExO5/z+ctiahI2c2vgOOlQczw/dvj6HQx65vDsvrXLzjBuaiERA1lli2Pn8r4GlBT7UVLAMx09AGh9GNAYAEd2+/tEksY7A17s6qwrXsHBB/MzwMi75PNQ10U+G9PDOV+2p8sCpYISLiQ66CTdJIEki1fGZuCbj2FvD+l6tteRYrso63sphkM7r5FHWbIoaeSCjGvGzhHHQmOj0CvJH3MrEA+TIXuWTM9F8YN3hvHh+xuwvtlU/Bpu/opky3C8cywaKmuA1Y8Q05IMuhuMmPSF4QsVH8zNCqYTuozUxObiyWGRwdjEqWSxSquCXqOEW8CC7G4GmRwKzQrmXMOiQwYAX9tDHMReem+kuPc1NQPh2WUlbrxiP0zyjlY9wNkhk6nuWEe9Hh++f/nrT4NJhwajLktBto1In1g4FgpCIk6Krs6DC80LVBqgYw8x9shSTF4dn4VvPoZdYpUrOo6lCvTHSUEGsDL2MFWqsWV1tXBzZGnLe2EkiydtHigoYNda8vfaXF0BjVKBwWLmyAyp746kOmQ3yH1nhXBOlzLFIxdkXELTJMdFinJFIMNpkb2xxz+dGkQoGsd/fayr+PenaeDWa0D7nvI+sfQ+BXj6Ae9d6VVPY4mNPXxjxNhAs7R7os0ZgE6tQEtNJT9rMDZyLhuzGHVwCShZdPrIe8szZCwJTZNHPTujhSZzBbasrsE7A0U6yxlT5zohZIuJGLkB7zwEKLi7BL91y4V+ZwDP7lvLKgNyc6t5sdMik50p1jmy8fOkm5TNCKXzEPn7ZORbGfQ5vKAoYOdakRp62N4gBXrTg0BdKjfOa2f10sfWWdHvDGBsmoPZynzxCRsK/bbNjQdXV8NUqQZADGtW11YW51isrwcohbQ6ZC7Z0KMckAsyLvGNk10VyRZkKfkaS2MPlz+Mf3tvBB/b3IROLroodz4AZkfLV67I0P04eczokvU2GAHc7Urxjm+claFHp8VQXMD3cjDh0BzKoywGLTwCdsiY+TWLXJCxI8R0yNjPnj7UXoubd/zFdZOZEFshZIujZ4CID+jmTgVA0zReOOHA6tpKPLWB3c3xphYzRqdDmApmfF/qugCdSbwFme0wUVB07F/8Z4wJlH2x2+Jpuwfrm0yoEWM2YDxK5uK6PkQKdI2eXIs97Aqy/alZweNCyBaZDQ0BZsjcgTCuT/ixp9uy4Oft9frinBaVKuI4LZUOWSxMXDkb5PkxqSMXZFzCBEJLtSBjDB5YGnu8cMKBJE3jvxzgoDsGkO4YpQS6n+DmeGLF3EIy6jLmyKxGLUwVaty6U6KCbHYsp7ubzcmTwyKDsYlIZOdncj+XJaLpkMm29+wITZFHFjNkDNvba0DTwIWR6cLfN+3yKUCHzHaEGNq07+XskCdtHlyf8OMP96yFSsnuss4ERC8whFAoyPzz2HnO1sYp9iNA2w5AZ1z8ZwYriZu5Z47MH47h8tgsdonV7v72u2SWktmoA0iXjGWHbE2dHh31ehwTQrbonwQ0VaSILzGnbMQF8d5oh/b6KoxOhxBPJAs/uJSyyDy3iNxVNvSQPHJBxiVj50nOlFS/GDozGYxmsWs8OhXCv58fw6e3tnIjaaNpYnfftjOnBXZZ0PMUMH4hfdKnKCpl7FECySJNk6J7mQ7ZzFwU7kAE3Q08OpKls8g4dFo0aOH2R0ALZErg9Ieh1yhRpVUJ8v6SI88ZMoAUEhqVAmeHpgp/X+MqAFTpO2Q0TebH1uzmzEWWpmk8f8KBJnMFPv4A+07F+mYTlAoqu2zRcwuYF8i5bymmBkmR0rWMEUrnQXJeDd0t1s8MTiGRpLG7U6TzY7bDJOalfc/dn9V1ka5Hkl1RcaDXinPDU/CHSzSDzOAbJ98lAYxSTto8sBi0WNe4sDhvr9MjlqAxNlOE8Y+hUToFmTMl0ZUt7yWPXJBxydh5ogFXqoVeSWFQFOsssm8ft0OpoPDsvrXcvLf7FjA1UP5yRYaeJwDQZHaA+VHKaZH3TJmwD4gGl3VYtKekk7x2yAxMQcal06IW87EEAhFhQj3lUOg8CU0BSu2ys4z3olMrsbnFjHPDRXTIlGqyC17qLDKvA5ge4tS06L3BKVwencXX9nRAzbI7BgCVGhW6rYbsxh4AMH6RszVyAiNFXE7q2XWIuP4NHE//6LTdA71Gic2t1TwvsABomhRk7XtJTiVDXRcQmyOOwyw4sM6KWILGaXuJs7P8k4LIFeOJJE47PNjTXb/INbO9nmx0FCVbNDRIR7LougGoK4HqNqFXIlMkckHGFdEQySBr2Zr7uWLG3JLT1MPhCuCXlyfwxUfauLP3vvUaAIp0jlYCll6ges0C2WJPoxFz0UTxlt65YOGwyBRk3XxY3jPw0SFLfR6Fclp0+sOwGlh8JwZPABd+wP+CxE5oihh65LnD/lB7LW5M+orrCBibAH+JO2RM+G82U4oCef64A1ajFr/1YP5Od5tazbgyNrtwE6jpQWJqILY5MvthktO13I3nqgeI/NVxd46sz+HFwx110KhEeLvjukGut/fGH6SdFtnJFh9orUZ1pbr0bov+CUEKskujswiE49h7z/wYAHQwWWRFWd83kvnWeBEB06XCdR2wrFvoOiojSUR4hpIok5dJng7jUiVVTC05O2TfessOvUaFrz3awd373nyNZMkYlg4zLSsoCuh9Ehg6BYSJTJEpfm7xHRDNIoPM5grAoFPx6xZYZSU3fhxa39cbUuHQfmHmyFz+cO75MZoGDv8f5J+wrzQLEyuhqbwMPRi2t9cgSQMXi5kjMzWVvkNmP0Ik7TnmN9lyfnga54an8dXdHdCp878h29xiRiAcXxikq60iaxRTQRb2Abffy13IKhRA52Op8OgERrxzGJ0OYXeXSOfHbIcBUIsLsvpUpidLYw+lgsLeHgtO9LuLm53Kh0SMyPpMpS/I3ra5oVJQ2JFlLtBcqUGNXlNcODSTRRYUKN+NLTRNMshkQ4+yQC7IuIIx9JBiIHQm5pZUPk92c4kPxmZx+LoTX961BtVcOVZ5BwD3jZUjV2ToeRJIxtJD6EzeF+8B0UzBbV5GsugMottq4DdEVakiRRmHBVm6QxYofYeMpmm4/RFYcmWQTVwiO9/JGGDPHmS7YghN5WXowfBAazU0SgXODhVTkLWQzYlSzRuGpoHRs5zKFV844UBdlQaf2VZYgbe5lRh7ZJ0jm3if5H6JgYFjZMOTTZB252PEKGj8IvocRMK3S7TzY28AzVuAqns6Pfp6YpTBskMGkDky33wM79/mziRpWQJOALQglvcnbR48uLoaRl328ZD2Oj0G3UV2yADxz5H5J8j9mlR9C2QWIBdkXDF2HqjpkL4hBdM1yTLs/uYNJz7/g3Ooq9LgSzvXcPeet14lj70rRK7I0LyV2OumZIt6rQqrayvRz3dB5hsjcztL3AjTNA2bK4AuPuWKDMZVrOck2GBJdchcAnTIZkIxRBPJ3F3FKz8h5j/6+pRUdwUz583L0INBp1ZiU4sZ54oy9mgC4vOcunwuywAT/suiqGDB5dEZ9Dm8+MqudlRoCpMrtddVwaBTZZkj207mTN03OVgpB9iOkM9JM4uRgI79xK3XcRSnHV601FSgrZanLMVi8N8BJi9l/zxQFFDXnVdBtrurHhqlAsf7SyRbTFvelzYU2ukL49YdP/b2LJYrMnTUV3HTIRP7HJnrBnmUC7KyQC7IuCAdCC1xuSKQNYsslkjiL39zE7//o/fRWluJ//z6DhiW2JkqiJuvAU1bcuZilR0KJbkYO94C4qSj02014BbfTotMBtkSobTuQAS++Vi6Y8crxlWcdsiqtCpUapSCdMgYy/tl5ypjYeD6f5DNh96nyE16jOeZQTETmmYdCn0vD7XX4NqED4FC58hKnUVmO0w2YFY9wMnhXjgxgOpKNX77odUFH0OhoLCxOVtAdErpIQbZYiJOVASdB9nNyVSYgdaHQNuP4szgFHZ1LjZ+EAXMPGGm3X0mdV15FWRVWhW2t9fg2M0SyeyYgqzEksVTdlJw3mt3n0l7vR7eYBS++QLPDVLpkDmvkUc5FLoskAsyLpgeIgOgUjf0ADKyyIixx+TsPJ558Qy+1zeMzz+0Gq987RG0crnbODMC3Lmy8uSKDD1PAtEAMHya/GejESPeOYRjCf7eM4flPSOZ5NVhkcHAbUFGURQsBq0gHTIm/2zZgsx+mEhMNn2GFGSxEDH4WInEoyQguYAOGQBsb68lc2SFSrSYnf1SZJElYsT5r+vgkhsh+XB9wocT/W58aeca6IuMWNjcaobNFcB8NOOcY24FqhrEkUc2fp58Z/KRenYeBOW6jqqIS9x299VtQH1P9j+v6yQzTHnEDxzotWLIO4fBYhwG2cLMX5ZYsvh2vweNJt2yG4ZFOy1W1gIKlQQ6ZNcB8+rsuXwykkMuyLiAuWiVQ4esqgFQqAHfON62ufHE832wOQN44TOb8T8+dn9Bg+PLcuvX5LF3hRZk7Y+SYM3+1wEQ6/skDThcPF5QfeMsLe95zCBjMK4ioahLzCwWgsWgE6RD5kp3yJaZIbvyMpHKrXkUaNtF5kSY78BKYz41/1VgQfZAazXUSqrwPDJmU6IUHbLRM6T45Gh+7IUTDhh1Knzhkbaij7WpxYxEksa1iQyDGYoiXTIxdMhsh8k1qWMf+9d0HgQA7FN9gIc7RDhGEJ0Dhk6S7thS3TvG2MPrYH3Y/b1Exnf8Vgm6ZP5JkltawlDoaDyJdwa82NNtWbbr2V6s06JCQe6FRN8huy7nj5URckHGBePnAa1x6Z0uKaFQgDY14eatG/jdH16A1ajDr5/biac28rQLdvM1ckKp4XAmTUqotGQIvf8NIJlET2puq58v2WI8Si4yyxh62JwB1FVpUVuVw5yCCxjLZI6zyIRwWXSlrPYtS9neB5ykS7Lx00R6pVSTkFvbG6SDstIoIBQ6kwqNEhubzThXqLGHvj69+cQ7tiOAUkPypoqk3+nH0RsufHHHmiVNDfJhUwtj7HFPp7FlOzB7W/ibUvsRoG1Hfl0ASy/cinp8TH8DpgoR5oIOvg0kIsvPE+ZpfQ8AzdWV6Gkw4Fgp7O/94yXvjr1/ewbBSHxZuSIAtNZUQqWgip8jE3OHLBoCpgfl+bEyQi7IuIAJhC6DHAiXP4wbc0aEPCP49NYW/OoPd6Tb/5zjnyTF7LqP8nN8qdDzJDDnBsYvYHWtHjq1gj9jD/8EADpnBll3Qwm6YwAvWWRMh4wulXteCqc/jFq9Zum8o6s/J6YOGz9z92e9TxFL75F3SrNIMRFKdbYKnCEDiP39tQkfgoUEgSsUqRlGniWLNE2kqmt2E0v5IvmHEwPQa5T4vR1txa8NQG2VFq01ldmNPQBhZYtTg6Qg6crPCGU6FMPR2EZsil1Jz+eKCtsbpLPU+vDSzzGvJkW815bXoR9bZ8XFkWnMzPGcoeWbKPn82EmbG2olhR1rlz9nqJUKtNZUFplFJvIOmecWCUGX58fKBrkgK5awnzhRlYFcsc/hweP/uw+OcFn1cccAACAASURBVDXuq/Thbz65gXuJYiZpueIKL8g6HyM79f2vQ6mg0GU18Gd9nyODLJmkYXcFSzM/BgBGZniau51Iq1GLUDRR2E16Ebj94aXnx2iayBWbt5HZEIaOfYC6cmXKFkPFdcgAEhCdSNKFW32bmvnPIvM6yJwxB3LFAXcQv7l2B194pA3mSo5iR0C6ZIsKssYNxI1VSNli2vgiv9/duwNenEhshiY5L77NjmSC/H91HiRd8qVQqohzcx6SRQDY32tFkgZO2nnukvknSx4K/bbNjW1ralDFYm6yvV5ffDi0mDtkzuvkUc4gKxvkgqxYJt4nuxQSNvRIJGl86y07vvAv51Gj12D31s2oCLv5T6m/+RqRedZ38fs+YkdnIrvn/a8DNI1uq4E/yaIv5Z65RIdsfGYe87FEaRwWAWLqAXDbIUvNcJV6jszpDy89P3bnCtnR3PSZhT/XVAJrD5Dog2SJAl3FQqi4GTIAeHB1NVSKIufI+JYs2g+TRw4Ksn88OQCtSsFt7AhIQXbHF047hQIgcupVm4XtkNkOA/W9xPwiD/ocHtzQbACt0hEXWzExfoF0h9nEH9R3AZ78OmQbmkyoN2hx7CaPBVk8SgxHSliQTczOw+4KYk/X0nb3mbTXV2F4ag6JZIFKCUMDMZMRqwuu6zqZPze3Cb0SGY6QC7JiGTsPgCK27RLEE4jgC/9yDs8fd+ATm5vx6rM7UNu0FgDNaT7UIoIeYPQ9Wa7I0PME2UX39KOn0QhvMAoPHwUFc/O5xIXUxhh6lCKDDADUOnJDzmU4dGqGq9ROiy5/BA2mJTpkV14m3Yb7PrH4z3qfAoJOYOIivwsUG8wMWUVNwYeo1KiwodlUeB6ZsYmc55I8uprajgDW9cvObbJhdCqEV69M4nPbV6OO4/lOJiD6yti9c2TbyGZCrPQzmZifJWYoeXbHaJrGabsXWzqbQLXtAhxH+VlfodjeIA5+aw/kfm5dF3EizkN2qVBQ2N9jwSm7B9E4T5s8wVQodAkliydtpMDc28PONbOjXo9oPImJmQILKrFb3zuvE7kiB66tMuJA/psslvHzgKWXZJ9IjDODU3j8+T5cHJnB335qA/7+6Y2o1Kjudk8yssg4p/910llcqe6K99LzBHnsfx29qWKIF9mibwyospJCKAuMw2KnpUQzZADn1vdMh4yXgnYJYokkpuYi2SWL8Qhw7RdA75PZzxOdB4lkdaWFRIemAJ2ZSLOKYHt7La6O+xCKFiBRNTUByTgQ5KmbEJoGxs7mXVRk4x9PDkCpoPDV3e0cLGwh61YZoVEqcDnbHFkiCtz5gPP3zMngcfJ3k+f82IA7CKc/jF2d9UDXIbLR5R3gaZEFYDsMtO1k505Y10XmTqeH83qLA71WBCNxnBsuIjh9OQSwvD9p86DJXIEOljPtzOz7YKHGHulwaBEWZDRNQqHl+bGyQi7IiiGZBMYuAM3SkismkzT+4YQDn/v+WRh0Krz67A48vSVj99bcSh59PBZkN18FatrlEwqDoYF8jvp/g24+nRZnc2eQNZkruA3+zgXH4dAWY+k7ZJ5ABDS9RAaZ/SgwPwNs/Gz2F1eYSfzBrV+TC+1KITRVlKEHw0PttYgXOkfGdxbZwDGy8VSkXHFidh7/cWkcn97akv58c4lWpUTvKqO4AqJtR0j3vDk/9ckpuwcAsKuzjsznAuLpknkHiEnJUmHQ95J2WsxPtrhjbR20KgWO8+W2yHxfjEtfS7gkEk/g3QEv9vawD/luryvS+t7A/XwzZ/jGSIyG7LBYVsgFWTF47eRLISFDj6lgBF/81wv45pt2PLVxFV57did6Gu6xE2bkbHx1yELTwEgf6Y6xPLmuCHqeACYvozbhQb1By4/TIosMsu5SyRUZOC7IDFoVdGoF3P7SdcicqeKvIdvN8pWXycW9YxnL854niTTJdYOfBYqRkLeo+TGGB1dXQ1noHBnfWWS2w4DeAqx6oKjD/NPJQQDA1x7t4GJVWdncYsa1cR/iiQyZW5UFqF5T+oIsEQccb6a6x/kZS/U5vGiv16O5upLMntV1k00RMcDME7KZHwPuGgDlYX0PkEiIXZ11OHbLxY/brL+0HbILwzMIRRPY281ufgwAavQamCrUhYdDi7lDljb0kDPIygm5ICsG5iLF7CKKnAsj03ji+XdwdmgKf/nx+/HtZzZldytS64isja8Ome0wkaLI82ML6XmKPPa/gZ4GHow9aDpVkGXf1Ywlkhj0lNBhkcG4itycc2RPTVEUrEYdXCWULDK5Z5Z7TT2CbnJjueHp5W8se54AQK0st8XQNFBZfIesSqvC+iZTYXlkzAwMHwVZIkZy57oOFjXn4fKH8bOLY/jUg81YZa7gcIEL2dxqxnwsAfu9ofQt28msdCm7t2PniKFCnp3FcCyBc8NT2N2ZMWfUdRC4/R6n4fMFYzucmidsZfd8jZ5soHnyK8gA4rY4PjOfngvmFN8EyV7NJxuuCE7a3NAoFXmFfFMUVZzTYkU1mfsVY4fMdR0ABVjWCb0SGQ6RC7JiGD9PvrS1a4VeybIkkzRePDWIT//zWWjVCvzn1x/B57avXr71b2rmryC79RpgaiUOXjJ3qVtLdnP7f42eBgMcruDC3epiCU0B8fklO2Qj3jnEEnTpMsgYmF1WDi98FkNpw6EZd7pFHbJrv0hljy0hV2SospBMopVUkM15gcrCDT0y2d5egw/GZzEfzdOcQ2cG1Hp+JIu33yMKijxnoO7lxVNDSCRpfP1Rfq8z6YDobMYec27SwS0V9sNkrrJjX14vuzgyg3Asid1dGYV+5yEgGQOGTnK7xnwJTadMSvL8PNR15t0hA4D9PaSbxIts0T9RUofFt21ubG+vITPuedBeV1V4ODRFiTeLzHUdqFnDSa6hjHiQC7JiGDtPcoVELLubDUXxlZcu4q8P9+PQfVb8+rmduL+JxTCxqYUfyWLYDwyeIM5yIv69CUbPE8DIu7i/JolIPImRqRB3x2YK7CXc3tIOi0J0yADO58hKaerhCkSgVlKovjcb6spPSWi8pSf3QXqfBNw3SBhuuUPTnM2QAWSOLJagcWk0zzkyiiJdMj46ZPYjZId9OalqDrzBCF4+fxsf29SE1tpKDhe3mNaaStToNbiyaI5MgIBo+9GU8UV+HZg+hwdqJYXtazI6Ka0PkW6O0LJFx5tknjDvgqybZJHlGYthMeqwsdmEt2668ns/NvgnSiZXHJsOYdAzl5dckaG9Xg+XP1J4JqVYs8gYh0WZskIuyAolNE12rUQsV7w8OoMnnn8Hpx0e/Pen1uE7n30ARrZmDeYWcpPCdTaS/Shx7ZLlitnpfRKgE3gwQm5+OHVanF0+g8zuDEBBgbWLFWcwO61cFmQGbUlNPVy+MCwGHRSKjE2GO1cB1zVg42eWfmEmPU+Sx/7XuV+g2Ij4SdeCgxkyANiyuhoKCoXPkXHdIaNpIk9bs5vIzgrke31DiMaT+MO9/M2OMVAUlT0g2tILaAylmyObGkwZX+TfWTxl92DL6hroM6X4SjUpih1vCWuaY3uD3OA3bsrvdXWdQGyuoBia/b1WfDA+C3eA43Ohf7JklveM3f2ebnZ295l01JPv3nDBxh4i7JBF54hzqFWeHys35IKsUMZTmUE5DD3iiSSShQYTFghN0/jBO8N4+sUzoCjgla89gi/uWMPanQgAkRQmImS2h0tuvUouShJzpiwZjZsBwyo03jkOpYLido6M6QIsIVm0uQJoq9NDp85viL5oGDcrLrPIjDrMRROF74zmSdZQ6CsvA0oNcP8n2R2kejXQuHFlyBZDqcKJo4LMoFMXPkdm5KFD5nUAM8PEdr1AZuai+NGZ23hyw6q0hTffbGoxY8AThD8cu/tDhZI4HZaqQ2Y/Qh7z/N25/WH0OwPY1ZWl69p5iGRnOa9ysMACiEdS84Qfyn+eMO20mL9s8UCvFTQNvN3PoWwxHiWzsSWSLL5t82B1bSXW1OW/sZG2vi/Y2KORBGCLCddNADTQIDsslhvFBcCsZMbOAZQSaFraPSsaT2LX356ANxhFXZUGFoMO9QYt6qu05DH1jyXj3/PVSN+Lbz6G//bKBzh6w4XH1lnxzU9thKmyAAvzzCyyqvylAlmJzgGOY8Dm35bDDJdCoQB6Hofy8k/QU/s73Dot+sbIvExFddY/truC6Cm1wyJAZEkaA+cdMoDcpFWV4GbW5Q8vdKeMR4FrPyf21vnMSfU+BZz4n+R3UcKMn5IzxxRk3EgWAZJH9q/vjiAcS+S3qWBqJjeY8Sig0uR+PhsYN70i7O7/5d1hhKIJPLuvdDPKm1vNoGng6pgPOzsz/m5atgOn/5ZIzvk2crAdBup7iUNiHvQ5yObhAkMPBsb+3v4m2fQoNSN9QDTI3u4+k/pu8uix5z1T19towCqTDsduufHMVpZGIrkITAKgS1KQhWMJvDfoxTNbWvLbUE6xurYSCgrFOS1G/EAkKJ55Ldc18ihb3pcdckFWKOPnyQ7FMnKUfqcfLn8ET6xvhF6rhCcQgTsQxo1JH7zBKBJZOmd6jTKjUNPdLdzuKeJq9RqolAuLmmvjPvzBy+/jzmwYf/5EL760M8+uWCbMnJFvFGh+sLBj3IvjLWIqsU4Og16WnieBC9/HRww2/NjJoU7cl8ogy/KZCMcSGJmaw0c2ClQEGFdxKhtj8sDcgUhJugsuf4QE0TIMvEW6QJtymHncS0+qIOv/DbDtK9wuUkxw3CEDgIfaa/DPp4dwaXQGj3TkUegZmwDQ5EYzzyJgSWxHUm56S0dMLIdvPoZ/fXcEH7qvoaQznRuaibHHlbGZewqybWT+aeL9ombicjI/S4wvHnku75f2OTyo1WuwrjFLwViVih5wHAUe/VMOFpontsOAupJIWPNFX09CpAvokFEUhQPrrPj5xbH8NyqWgtk4K4Fk8dzwNMKxJPb0FLYprFUp0VJTiUFvkVlkQZeICrIbZCaSrVOnjGSQC7JCSMSB8fdz3mx9kNLi/1+P95BMlMxDJGnMhKLwBCJ3/wlG4PaTR08gjH6nH32OCPzhxbIrigJq9RrUpQo1U4Uab95woa5Kg5999WE8uDp7F4Q1jKyNS2OPW6+RHfHWR7g7ZjnSthPQmrA7cQ5/Pd2OYCSePZ4gX3zjS94gDriDoGmUPoOMwdjIS4esFHNkwUgcwUgcDaYMh8UrL5P8qY79+R2svhuo7SSyxbIuyFJSaD13BdmWtprUHNl0fgVZ2vp+gpuCLDQNjJ0Fdv1JwYd46b0RBCLxknbHAMBUoUZHvX7xHFnzFgAUkS3yWZANHCORKHk6UyaTNN4Z8GJXZ93COc5MOg8Cp/4XcffkyEyGFcw8Ycc+EimTLxSVMvbIvyADyBzZS2du471BL/b1WAs6xgJ8TAYZ/wXZ2/1uaFUKPNxe+Hmiva4I6/t0FtkdoJb/OU5WMIYesila2SEXZIXgvkGGbHPMj30w7kOtXoOmLNkxSgWFuiot6qq06G1c/u3CsUS6YFuqgBvyzGF/rwV/9fH1qNZzILupMJNdGK5mK2JhYuhx/ycBpfyxWxalGug6hA7bm1DiadicgeILbIAU10vIdRjzkJI7LDIYmzi1pbakOmSlcFpkir70DNmcl8zBbP9a/p91iiKyxXf/dyqnixtbeNHBQ4fMqFPjvlUmnMvX2IPZfOLqXOd4i3STCrS7D0bi+MG7w9jfY2HniMsxm1ur8Xa/GzRN31VY6EzE3INvYw/7UfKZaN6S18tu3vHDG4wu7FLfS9dB4NTfkFmujc8UudA8uPMB6f7v/bPCj1HXRbruBfBQew30GiXeuunmpiArYSj0KbsHD3fUFtXZa6+vwpmhKSST9NLF+lIwHTKxGHskk6RDtvHTQq9EhgfkO+NCYIabczgsfjA2i40t5sJlgyl0atJ2b6nh1/Z4EVxmkQ2eIBp6Wa7Ijt4nobn2c2yh7Oh3biy+IIvNk67EEoYedlcAGqUCbTxbay+JcRW56CXinBTsRp0KWpWiJB2yuwVZavf72itklz9fuSJD75PAO98iRV2hxxA7oSliCa/hVga0fU0NXjp7Oz95Vtrlk6OCzH6YdEcLzFn88dnbmA3F8Nz+Tm7WkyebWsx45f1xjM/ML7zmtGwDrv8nuSnkYwY4ESfW8N2PLx+ingVmfmxX5zKdr8bN5O/FcbS0BZntMACqKIMX1HcBV35MJJ0V5rxeqlUpsburHif6XUgm78+/KLkX/wSgNQFafjfvhr1zGPbO4YuPtBV1nPZ6PcKxJO74w1k3x5cls0MmBmZvA9GAbOhRpsjOCoUwdh6osi6r4Q1G4hjwBLGxOb+Tp6jgMovs1mskhHXNo9wcr9zp2A9aqcWTmve5sb5n4bDYYalaNJdYMgyNJEB5jhs3MIqiYDXq4C5phyxVkH3wMrG2LjQnZtUDpEgoZ7fFuSnSCeFYdvNQey2i8eRiyd1yaCqJ0Y2PgxnGeDTlpnewoKJlPprA9/uGsKuzLh3UXGruBkRnySOL+AFPPz9vPHYOCM8C3fkboZy2e9DTYEh3xrOiUBBzj4FjpPgrFbY3yO+uGJlk2mnRUdDLD/Ra4fJHcH3SV/gaGEpkec/Y3ReSP5ZJex3Z9CnI2ENrIEZYYumQuW6QR9nQoyyRC7JCGD9PdguXuZm4Nu4DTQMbWkovOeEMcwsx9SiWeJRclLofJ3I8mdxoq0B17MUh5UX0T3Jgfe/LnUHWbRVwaDndpeBuJ7JUWWQuPyn6rEYd0fff+aC4zhYjWxw4Tty9ypHQFKfzYwxb19SAKiSPzMhRFtnoGVK0FChXfPn8KLzBKP5IoO4YAPQ0GKBTK3D53pDtdEA0T7JF+2FAoQba85tRC0XjuHh7Gru7WORUdR4Ewj5yDS8FvnFitd9TgLtiJkVY3wPA3h4LFBRw7BYHG16+8ZLIFU/aPGiv0xcdiM5kkRU0R0ZRqSwykXTIXNcBUEQ+LFN2yAVZvgRcwMwI0JxDrjhOdhcl3yEL+4jVcTGMnCbHkeWK+dHzJCxJN2jXNdDFBpoyHbIsph7+cAyTvjC6hDL0AO5e4Dl2WixFh8zpC6NKqyLGKx/8lNxU3v+p4g7a8yTJARw4xs0ixUbIy+n8GIOpQo11jcb888hMzdzMkNmPEClmAcYX4VgCL54axEPtNdjaJtzsoEqpwIamLAHRNe3k74yvPDLbEWJolKet/rmhacQSdHa7+3vp2AsoVEQaWQpsqfiDQuzuMzGvJpmGXltBL6/Ra/Dg6mocv8VBppZ/gndDj/loAmeGprCnyO4YANQbtKjSqorLIhNLh8x5jZiLFBE2LyNe5IIsX5idtVyGHmOzaK2pRA0XBhtCwXRTir1RufkqmRXJc+dzxdP9YSShwM74WdzxFdnpmR0DKMXdIeUMHC4iiewWytADyOiQcee0WG/Qwu3nvyBzB1Kh0IkYcPXnZFak2O5P68Pk5rdcZYuhKU4zyDLZvqYWl0ZnEIkn2L/IxEE4NOOmt2Z3QTdMv7g4Bncggj/aJ1x3jGFTqxk3Jv0Lf4cURa57fHTIpgaBKQfQnX9n8ZTdA61KgS1tLOZsdSby3bKXsCCrXQvUFfl3qlQBNR0FSxYB4rZ4Y9KPydn5wtcRjwBzniWVFlxxdmgK0XgSe7pZFNk5oCgKHfVFOi2KqUMmyxXLFrkgy5ex82SnKke45NVxHzY0S1iuCNydkSvG2CMRJ5lKXR8qzPJ3JaOvw5z1QRxUXCx+jsw3DhhWZZWM2pxk51Awh0WAuAkqtanQUW6wGnUIRuKYi/A7L+L0hYlcceA4mYHb9LniD6pUkV11+1FyE1RuMDNkPPBQew0i8SQ+GMtjXsbYROaXogXetAFETjYzXNAMVDSexHdPDuLB1dV4uIOf30s+bG4xIxpP4tade847LduA6UHiJMol9iPksYAg7T6HB9vb83Di6zxInJK5jHTJRtgPDJ8uqMjMSn0X4CmsQwaQOTIAON5fhGyR2TDjWbL4ts2NCrUS29Zw0ylur68qLhw64CQbLkISCRB1lmzoUbbIBVm+jJ0nxdgyxYU7EMbE7LxgQ9mckc4iK2KObPQ9shsuyxULQn3fR9CrGMXE8M3iDsSEQmfB7gpAr1Hm70DFJRTFWxYZ37JFlz+CBqMOuPIT0vXpfIybA/d+hDhqDZ3i5nhiIREDIj7eCrJtqTmyvOzv02qAIiSzjDytgKLiPy+NY9IXxnP71hbtyssFm1pTAdFLzpFxLFu0HQYs64Dq1Xm9bGJ2HoOeOexezl3xXhi3Q75li4MngGSseLkiQ10XuSEvcIOmo16PttpKHLtZhGwxXZDxJ1mkaRpv29zYsbY4u/tM2uv0mPSFEYoWsDlnaARiITIbKiSu1D2A3CErW+SCLB/iUWDyck654tXUzuxGqRdkVVYyD1NMh+zmq4CqAlh7gLt1rSB060khqx86WtyBlinIbM4AOq2G4u2Qi8XYxG1BlsoFc/No7JFM0nAHwmitiJBd/g1Pc2dc0/4ooDEA/WUmW2QyyHgw9QAAc6UGPQ1GnB0upCAr4lxnPwJY1+ct54onkvjHk4PY0GzCo2yMKUpAo6kCVqN28RzZqs1kBotL2eL8LDFDKaQ7ZvcAADtDD4a6LqL+4Lsgsx0GKmpyzpuzpq6LONFODxX0coqisL/XijODU4WrBvz8h0IPeecwNj2PRzmYH2NoryeGVcPeAjrgaet7gefIXNfIo1yQlS1yQZYPzqtk0L5567JPuzo+CwUF3Lcqv+Fk0aFQFDdbkUwCt14nHQN5CLUwqtswqu7A2ukiuiTJJNn5z2LoAZAOmaDzYwyGRs5NPQDAxWOHbCYURSxB46HQCSAR5TY3TKUl9un9vwGSecxDiR0eQqHvZfuaGrx/ewbReJLdC9IzjAV+/kLTpEgpQK74+tU7GJ0O4bl9naLojjFsbqlebH2vriAKES47ZAPHSG5fAQXZSZsHDUYdOi15OMRSFNB5iHSeYzxt1iTiJO+s6xAnuYoAinZaBIhsMZpIos/hKewA6fgU/gqyt1OSyj0cbk60F+O0mA6HLu0cGU3TeOnMCO74UjN/zutkBpLn+T0Z4ZALsnwYY2focWXchy6rAZWaMsjdLiaLbPw8EHQC6z7K7ZpWGGOWvVgXv4mor0CpSdBFpDNZTuTeYARTc1FhHRYZjKuI7T1HWv20ZJHHDpkzdewe129Id6RhPbdv0PsUKWBGz3B7XCFJF2T8mHoAJI8sHEvi6jjLPDLjKgBU4ZJFx1sAnSzI7v7lc6Noq63EgV7uOgJcsKnVjNtTIUzPRRf+Qct2YPISkZ5ygf0IKc6bt+T1spm5KE70u/Gh+xvyL2S7DgHxeWDknfxex5axc8D8DHfzY8BdY5AiCrItbdUw6lSF29/7J0meKI8brCdtHnRaqhaGkhfJmjo9KKrQgkyYDtmwdw5/8eoNvHgq1RF1XSfXGBFt2shwi1yQ5cPYOVKgGBc71THQNI2r47PStrvPxNxauIzn5mvEAKXzILdrWmHEuh6HkqLhvfRqYQdI72ouDjK3O0XgsMhgbCId6FCeluVLYKpQQ6NS8DpD5vZH0EmNwzxzjdvuGMPax4jZya3XuT+2UDCGEDx2yBgzgHPDLD9LSjWRaPsLVAPYD5PXr9qc18uGPEGcH5nGM1tbRdUdA+4GRH+wKCB6GxAPE8VIsSTipJjtPAQo8psX+tWVCUQTSTyzNXvnf1nadhIpvaNIKfhS2N4g176OfdwdU6Mn9x+ewgsytVKBvT0WnOh3I5EsYOOLZ8v7uUgc54enOXFXzESnVmKVqQJD3gKMPdIFWWk7ZEx00vF+F+hkgsyQWe8r6RpkSotckOXDWCoQehlGp0OYDcWkPz/GYGohO0PxaO7nZkLTwK3XyAUpz1wZmYU0dW/FWLIeVH+BN+VMuHeWDpktZXnf1SBgKDQDs9HBkWyRoihYDFreO2SfVJ4GrVAB63+L+zfQVpHv0K1fC+/yxRXpGTL+OmQ1eg16Ggz5BUSbmgvrkMWjxGGz8yCReefBzy+OQ6mg8MkH+c11KoQNzSYoKCwOiGZmoriQLY6dI+6WeUo9aZrGzy6MYUOzCb2NBVxf1BUknsB+lPvvFU2TgmzNbkDL8UZXXWdRHTKA2N9Pz0VxZWwm95PvxT/Bq1zxvcEpRBNJ7OVwfoyhvV5fWBaZRg9ojSXvkF0ZJQXZ2PQ8RgdvALE52WGxzJELMrb4xokldy65Ymo3cWOLxC3vGcwtAOj8b5InL5HOmixXLJq2+ioco7eg3n2GWN/mS7pDtrggs7sCqK5Uo75KW+QqOYDZeeVwJ9Jq1MHFYxaZ2xfEx5XvgF77GFDFkyFD71OkczN5mZ/jlxqmIKtgkRtVBNvX1ODiyAxiCZZzZIXOy46+RxzY8pSnxRJJvPL+OPZ2W2AxiC8SpFKjQneDcfEcmamJbNRxYexhP1xQJ+nquA/9zgCe3lJAd4yh6yAwe7uobK+seB3EeINLuSJDXTc5fpLlZzoLj3bVQ6Wg8NbNAmSLvgleLe9P2tzQa5TYwkMwekd9FYY9c6ALKcAFyCK7MjaL9joiDbVdOUt+KBt6lDVyQcaW/5+9Nw9v6zzPvH8HIAmSIMANABeRWkhxs7VQtmzJ8SZL3uTESZqkseMuky5Jl69pp820zXydznxt035fp9sknfZqs7XTtPESp2mcxLKdSJa3eJFskZIsidROgBR3YiFBkARwvj9eHAriBoA8AA6I93ddvo4tAgevKQDnPO9zP/etXXwSGnr4sBSYspvppCerdR8785xw40rHRSnPKDSbOFt+DwVqbCc+VXweMQy8RKeyZzBAa43NGHIp7UKvo7GHy2ZhOJC+Dpm9/3VqFC+mXTpkjy1H20FQzLDaDqnRCI6JORS93CiXYW9TNdNzEU56kswjszeI916qN2w9LwhZadO+lJ72ZR0zbwAAIABJREFU8rlhRidnVie5yxCdjRV0u71EF8rbGm/Xp0PW84KQD6bYSXr6uJviQhMf7lxDcdCi2d/rLFvs+aE4rmKeMCGOFtEpWUNeY3lJIbdvqeLw2RRnkudCEBwVn5M0oKoqR3tGuHOrg6IC/W9Nm51WpmYjq9ug07LIMkRoLsKZa34euLmGjjo7/qsnQDGBqyNja5BkHlmQJYv7mNCcJxja73Z72bahnELzOvnVzmeRpVCQaXLFLfekfRc8X4g23M4EduG4lype9/W/xzhUVaV3aJI2Ixh6gJjBUcy6Wt/X2IsZTmOH7KbhH+JT7Ndv7tJBaRVsvlPIFtcDU6NpnR/TuD5HlqRssXyDyBuaTkHKpaqiy7PlnpSNDp457sZls3CfzvMyerJrYwX+UJhLC+3CG/eI4nW1DrwAYxdh7HzK7orB2TDPdQ3wyPY67MVrKOorGkX2Wa/eBdkhqOtMj7RPc1pcQ0A0CLfF88OTXB1LweQikN5Q6PPDk/R7p7mvPT3mNpr1/aoCom11Ge2Qnb3mZy6isquxggPtLsr9vUSqtgqprWTdsk6qhgzgfhs23LLirm44EuX0gG/9GHrA6jpkQ6eFZEPKFXWjtb6SH4V3Ee19IfV5Pp9nyYJswBdiciZsnG6uyRwzVtDvwue0WQjMhJmeTYNt/PQEu4JvcKxsPxQU6X/+eDo+LGZH1ngjZgiCY2mdH9OoLrPQWlPGW5eSNPbQvutS6dCO9oqw3hRnoIb8IV7uGeHjtzZQYODNu12xWehFeWTaLPVaZIurDNJ+/tQgkzNhHluLXFGj5QHhYBpKsouaiMkR0TnUKwx6Ic42cVyjzPL+jhoAvvNuCgW1Nl+Zphmyoz0xu/s0bVBo1vcXV5tFFhjM2Byv9nnrbKxkf4eLdq5yrbg5I68tyR7GvRIYiblp4SiVwNCjd2iS0Fx0/cyPgchCKqtNrSA785xor7d/KH3ryjPaau28FN2NacYPV1O0avb1LT0/pjksGqVDBjHre/2zyNIiWzz97xQxx9maR/U/90LaPyiOZ59L/2ulm+BYRjpkAHu2VPPulfHk5sg0KVYqXZ9VFhXPvushElXXNgOVAZqdZdgsBYsNIGq2QWHp2mSLvS+IDlXlppSe9swxN1sc1vkO6JpoeUhkoF06uvZzQUz+qKZPqm91Cvn5Go09NlaX8sEddfzd0Yu8ezXJjrCmXEiTZPHlcyO019qoK09PF6jWXkxpkXn1HbLIbGrd8zXQ5fZSay+mtryYTodCo2mEEzMyf2y9IwuyZBg4Ib60Exh6aDal66pDBuJmPhXJ4tnnYNOdGdkFzxc6am28Ft3OnKk4NdliyC92f1dyWHQZrSDTT7KoZZGlw9gj2vUk56KNRGt26H7uRdjrYcPu9WF/HxwTMswMsKepiqnZCKf7k+iAaDv/qRRkvS8IGXsKYa2qqvLt4272bKliiyN9eU56YDIp7Ggs50Tfgg6ZuRA23Lr6Dtm0F67+JOVCVosJ+OTuRn3mXhv3iAKn96W1nwtEgW5v0D+PUENRYsYeayvIAP7sp7ZTV17Mbz55At90EplyWiREGiSLgdAcx66Msy8N7ooaiqKwxWFdYxZZZmSL3W7v/Ma+aeQMAIdGqwkna1AkyUlkQZYMSRp6dLu9lJcUsqlav0BDQ1DRmHyHbKQHRs4JiZVEN5w2C6WlVnrK9oiCLFmXLa3bVLF4J753MECtvZjy0vSaK6SEvV53l0VIQ4dspBdT/zGejdxDTXmGHPI6HoVrXeDty8zrpQNVjc2QZWazZs8W0YlLKo/M6gJTYfId2uC4uDakaN7w9uVxrowFDW3mEc+uxkrODQYWy34bb4drJ2F2FTe4F34MaiTlTtLTx936xgSYC6D5AJx/aU3OhYBQ0lw8EjPhSaNJkqNVl4KsvKSQL39qF0P+EF/4zsnE7oP+ATETXqT//c0bF8YIR9W0yRU1mpxlq8wii0WyZKAgm5ia5cpYkM7G2Pz94GkA3g01JN/NlOQksiBLBvcxqGpO2PHp9vjY0VBuDMc6PSlvFLvGyVywzsQkVR0ZkHHlEYqi0F5r58fqbnFRSNYCXetsLjFD1jMUoNVIckUQBdmMX3T2dCBtHbLub6EqZr4XuTOzBRnkdpdsJgDRuYxJFp02C81Oa3J5ZCaTeP8lm0V2/iVQoyl3eZ4+5sZmKeDgtrqUnpctOhsriERVTg8s6DI27hFF1WriGHpfEEX5hluTfspcJMp33u3XPyag5UGYGhabHWvh8qvCFCbdzsLOVpgcEl3GNXLLxkr+y0NtHDo9yLfeSbDR40tfKPTRnmFslgJu3ZReE7AmhxXPxDShuRRniuc7ZOl3WuzyaPNjMaXV0GnU4krGzVUcObeKqAJJzpCwIFMUpUBRlD5FUY7G/tmuKMofKYpyTFGUv8vEIrOKqopd0ATzY9OzEXqHAtc/ROuJio1CPz2VxJfB2e+JC7U9N242con2OhtP+W5CTcUC3bd0QRaJqpwfnqStxgCB0PHonEVWUVpIkdmkb4csGoHupxmpuYsRKqjJVIZUdbOYucll+/sMhEIvZG9TNcevTCQn9ylvSF6y2HNImNDU70p6Lb7pOZ4/dY2P7KqnpMic9POySedGcU1bHBAdU4ykKluMhOH8j2JB2sn/DrSYgMf17iy2PAAoosBeCz3PQ5FN2PinE81pUaf8tM/e3cTdLQ7++PtnODe4wkaY35OWgkyzu7+rxZF2d+ompxVVhSupuEuCmKOHjHTIut1eFAW2N8S8CIZOo9RuY88WB4dlQbauSebdvwN4UlXVfaqq7gOKgLuA24FhRVHuT+P6ss/4JZG9kaAge3/ARySqrr/5MYhzWkxwozJ+CQZPSblimmivtTE4W0Jowx2pFWSmQnHjGMfVsSlmw1HjOCxqaNIQnYw9FEXBabPoa31/6SgEBjjtEqY1tZnqkIHokl39CUzm6IVZK8gy1CED2NNUzeRMmPcHkui62jdcn5VZifCskKe1PCg6a0nyXPcAM+Eoj+3emPRzso2jzEJjVclip8XSKlEcpGrs4X4LQt6UnSmfPiZiAnSXtVljnbq1FGTRqMhU23pAGGGlk/mCTB/HVZNJ4a8/2YmtuJDf+NYJgrPhpR/oH0iLw+K5wQCD/hD3pXF+TKN53vo+xYKssFjINTPRIXN7aXXZKLMUiM2/oTNQu5397S4upBpVIMkpkrmS7AU+pCjKO4qifB04AHxHFYLjF4G707nArOM5Jo4JDD20i9WO9eSwqDGfRZZA0iDlimmlvVYEO1923BezQE9ijsDnETKsBTeNvUMGdFiEuHBoPefIdA6H7n4Siis4btlDkdlEZSZn8DoeBVSxG5+LzBdkGeyQpZJHVr5BvPcSybP7fiKktanOQB3ro6POzrYNi0PajUxnYyVdC409IBYQ/XZqduA9h8BcBM37k36KiAkYTl9MQOtD0P+esK1fDddOwORg+uzu46nYJH5/OsyRaThtFv7XY51cHJnkj79/ZvED5qbFZzcNhh4vx+zu781AHp9mfb/6LLL0FmSqqtLt9l5XWo1fgvA01GzjQIcoWKVscf2SzDfbMeB+VVVvBwqBEkDbvh4HahY+QVGUzyqKclxRlOMjI6v8gjMK7reFDMHZvuLDuj0+6suL9dW2GwXNECKRscfZ54R8J0UbY0lytNbYUBR4szC2OdCThNuizyMkpwvoGZxEUWCry2CSxfkOmZ5Oi8X6zZCFfCKgefsnuDap4rJbMjszWrMNKjfn7hzZ1Kg4ZshlEcBlL6bJYU0uj6y8Qcy4JZJn97wAZgs07Ut6He8P+Djd7+ex3Q05N2fc2VjBgC/EkH/BxkbjHmEFPnYh+ZP1vihkfZbkN4OefddDVCV9MQEtDwAqXPjR6p7fc0iE2rc8oOuylsRcIGbadZIsatzV4uDX7m3mqWNunute8P2bRsv7oz0j3FRnnzdgSielRQXUlRev3mkxzZLFq2NBJoJz7IybHwOgdhubqq00O62yIFvHJFOQnVRVVXsXHgcmEUUZQNlS51BV9Suqqu5WVXW305n+XY+04j4GDbsTat1PerzsWI9yRRC2wJbyla3vfR7of1fKFdNISZGZzdVWjk+UisI3mZtyr3vpDLKhABurSiktKkjDStdAYbHonuiaRWZheOGN5Gp5/7sQDkHnEwz6Qhm5ibgBRRH5fpeO6hdmm0myMEMGQrZ47PI4kWiCTk4yWWSqCr2HoOleKEretv6ZY26KCkx8dFd6jBHSya75ObKFAdGxzaFk58jGLsLY+ZScKaNRlWfSHRNQu1PIuntfXN3zew7Bxjsyt9HgbE1LSPxvP9DKLRsr+L///RR9Y8HrP9C+j3XukPmm53j36gT3tWfuPrHJaV1lOHT6O2TdCw09Bk+LQt8hAsEPdNTw1qUxJmeWkZVKcppkCrJvKoqyU1EUM/BRwIqYIQPYCVxJ09qyz0wAht9POD82MTXL1bHg9V2N9UiiYfez3xfHmz6SmfXkKW01Ns4NBkRQcP/xlaV9kTAEBpZ3WDTa/JiGvU7XnUiXvRh/KJy6s9ZSdD0pLo71tzAUCFGb6YIMxKZHdE6/7KRMEhwVcquizHZm9zZVEZgJcybRHFkyWWQjPTBxRcjckiQ0F+G7J/p5+OZaKkqLkn6eUbipzk6hWVk8R1bdAsUVyRdk80Hayf/u3r48ztV0xwSYTKK7dfFliCSRyRXPxFXRyUi3u2I8jlbxHgzr6x5baDbxpcd3YVLgc0++x2w4Jt3VOmQp5O0lw+vnR4lE1YzMj2k0Ocq4NDKZ2OZ/IbZaUZCtNR5hBU70eSkpNNOqmW0NnRZ/14XiOrO/3cVcROX18zmuPJMsSTIF2R8D3wS6gDeBLwK7FEX5EvAF4Mn0LS/L9L8rbI0TFGTzgdDrcX5MI1EW2ZnvCTlVdXPm1pSHtNfZuDI2Rag5Nquw0ixRYEC8fxdcRGfCES6PTtFm2IJsg64dMs36fs3GHmMXhSFB5xOgKAz5QrjsaR7gX4qG28Ru/rnvZ/6110pwTBh6ZFiydz2PLMEcmeYit9L7r1crKpI3pXjx/UH8oXDOZI8tpLjQzE119sVOiyZTbI4sSWOP3heEU2gKsvZnjmcoJqDlIZjxpe4a2fuCOGa0IGsTkQPjl3Q/dWNVKX/+8R10e3z85UuxLpy2QWHT9+/gaM8w9uKCjLpTNzmtBEJhRidnU3uirU78zoOj6VkYwotge0P59TnJwdNQu23+57duqsReXMDhs1K2uB5JWJCpqnpaVdUdqqpuV1X1D1RVjQL3A68BB1VVvZz2VWYL9zuAAht2r/iwkx6fsCndsI4LsvLG5SWLgSHoe0vKFTNAe60dVYWeSL2YI1jJbVG7iC4oyC6NTBGJqsbLINOw1+s7QxbrYg2t1dij61ugmGDHY0zOhJmajWSnQ2YyiQ7p+R+JYftcYmoso4YeGrXlxWyuLk2cR1ZSCYWlK2eR9b4ItdtT6hY8fcxNY1UJdzRlzl1Sb3ZtrORUv2+x7LPxdhg5J2bJVmJ6QjiEplDIZjQmoGmfcKRNVbZ47odixjyTm5GOFnHU0dgjnoPb6/jZvRv5yquXhOmGvx9KqnQNhY5GVY72jnBPqzM9Ri3L0DTvtJiisYctvdb3s+EoZwb8ojiNRuHVvxCOr3Wd848pNJu4t83Fyz3DRBPJryU5x6o+BaqqTquq+qyqqvpvzxgJ99vii7Zk5d2bbreXZmcZtuIMuq1lmopGsXu41NzKue8DKtwkC7J00x4ronqGJsVN+eVXlw8I1QqyBaYe8w6LRu2Q2epFJ2VOn7mvGrsOHbJoFLqfEs5w9joGfaHYubNk4tPxqAihvXgkO6+/WoJjGTX0iGdvUzXvJJojU5SYPHuZzafguLgupDAD1TcW5CcXx/jkrY2YTLll5hFPZ2MFwVje5g1oc2Se4yuf4MJh0WFIoZP0XFd/5mICiu2w6Y7U7O+nvXD1jcx2x+B6QZaM0+4q+W8fvIn2Whuff6abmXG37pb3Z675GQnMsC+DckUQ4dAAF1M19tC6g2maIzt7zc9sJMrtrij82yfgyBdh28dh9y/c8Lj7O1yMTs7OK7Mk64fMbUvkGtGosLxPIFdUVZVuj3d95o/Fs1IW2ZnnxCxBAidKydrZWFVKSaGZs4N+cVMeDcOFHy/9YC2mYEGYZ89ggAKTkr4B+bWiDY7rtBOpOZ8ucohLhSuvit3KzicA5k1CslaQbb5bmO2czTHZYnA044YeGnuaqvCHwpy9lmCObCXJ7PmXhAw4hQytZ467MSnwid36O9RlEk1WtsjYo/4WYTyQSOrX+4Lojm64NenXfPq4O7MxAS0PiW7fxNXkHn/hx+I7OBN29/EUWYVqJU0dMhAy1f/9xC6mZyNcc19Etelr6HFUs7tvzazx24aKEiwFJsN1yLrcXnYr57jv6Mfhyuvwob+Bj399kXHQva1OTIq0v1+PyIJsOUZ7RTcoQUE24AsxOjm7vufHAMpjO5QLZYtTY+LL46aPZHwuJB8xmRRaa230DAaElNbqWv6m3OcRN0ALZCa9QwGanFaKCgz68Z/PItNHtlhZWkihWWE4sIYOWdeTwmm07YMADM4XZFmYIQMwF4ouTc+h1E0Isok2Q5YFrs+RJbC/L9+wvGSx55CY36vbldRrRqIqz77r4d5WJ3XlJYmfYGA2VZdSWVpIl3uBNNFSJuZcVirIImEhsW19KKFjscbpfhET8PhtjZmLCdDMRpLtkvUcAqszpSJTNxwtaS3IALa6bPzRh2/GPjvM6Ul9FRUv94ywo6Ecpy2z36Gm2GbkpVSdFstiCU+BIf0XFY1SfeLvecryRUxFJfDLP4Ldv7jkPVVFaRG7N1XJObJ1iEHvyAyAJzaknCAQujvmOrXuO2TLZZH1/FDIUKRcMWN01AqnRVVRoP0RsUu7lLzPt7TlvaEdFiHOWEGfgkxRFFy24tVb34f8wrRm28fm3a60XLPa8izmDnY8CiGv2BDJBSJzYpMrCzNkAPUVJWysSmKOzN4Ak0MQXjD0H54VsruWBxcFrS/Hq70jDPpDOWvmEY+iKHQ2Vix2WgRxnfS8KwqvpXC/Jd6rKcyPPXM8FhPQmcGYgOqtULkluYIsMpdykakrjjaRRZZG1z+An95ZRZUyyYtuM8euJJHllwTe4Cwn+ibYl+HumEazsyz1Dpm5UBTfenfIguPw5GN8aOQf6bLejfLZV6Bu54pP2d/h4sw1P9d8OTZDLFkRWZAth/ttMeBdvXXFh3V7vBSZTbTXGfgGVw+sLmFXrcngNM48BxWboHZHdtaVh7TV2hifmmVkcgbaH4XZSbj8yuIH+jyLCrKpmTDu8Wnjzo+BsL0H4RKpE06bZfUdsjPfg/D0vFwRhPzRVlyQ3Ry35v3CgCJXZIvB2M1clmbIQNjfv3N5fOWB+PIGQF1843X1DZgNpDQv9NSxPqqtRexvr1ndgg1GZ2Ml54cnCYQWdGUbboe5KRETsxQ9h8T1o/m+pF4nNBfhP2IxAeWlGZzNVhRRcF9+FWaDKz/26k/EXHWm5YoajhbxO9fxe3IplNjMVKi0lt968gTeYIruhEvw6vlRoirsa8/s/JhGk9OKe2L6uq1/smjW93rR9zb8w12ol47yh3Of5u1b/0rMMibgQOz3JmWL6wtZkC2H+x1xkUkgleh2e+mos2EpyMIOWSYxmUTnIn6GbNorAmqlXDGjtNeKL+xz1wKw5W4osi12W1RV8Xe1wNDj/LDYFTSswyKAxQYWu65OizV2y+pnyLqfFBszDbfN/9GQPwuh0AspKoWt9wuXtzTvkutClkKh49mzpRrf9JzI8luO5bLIel8As0W48SXBSGCGw2eH+dgtG4wrD06RXRsrUFXhLHwDmrR/Ofv73hdg813is50EWY0JaH1QhL8n6jz3HIKC4qTfD7rjFGHB6QiIvoHY5+BT9+9lZHKG33v2ZOoZXgs4em6YytLCrCmLmpxWIlGVvvFVGHvo0SFTVXjjy/DPj4CpgPceeIZvRh6kc2NlUk/f6iqjsaqEI1K2uK5YH1cJvQmOC212gvmxSFTllMe3vgOh41mYRdb7ggiolWHQGUVzWjw36IcCi7iB6DkE0bjg4+kJ0Tlb0CHrHTS4w6KGvV7nLLLi1XXIxi+Jzkgse0xj0J+lUOiFdDwKk4MiJNzoaPk9WZohA2HsAQnyyOyxz0z8+09VxWes6d5FQ/bL8d0THsJRdV3IFTW0a90i2WLFRiirXXqObPQCjF1IyZnyqXeyGBOw6S7ReT6/gv29qooMyKZ9Sb8fdMfRKo6j59P7OrHPQXNzG7//cDsvnRnim28laXqyBNGoyisxu3tzllxHmxzC+j51p0UdOmTBcXjyU/CjPxQS3l95lTemGlAU2NGQnBeBoigcaK/h9QujTM9GEj9BkhPIgmwpNPveBAXZpZFJpmYj639+TKN8442mHmeeE12z+luyt6Y8pNJaRI3dcn2Xv/2DMDVy4+70fAbZjTeDPUMBigtNNFbplyeTFmx14NdPq19jt+CbniM0l+LFq/spQIEdj9/wx8P+meyEQi+k5UGRnXT2uWyvJDFahyxLM2QADZWlNFSWrDxHtlSHbKQHvFeTnoFSVZWnjrm5dVMlW10G3/xIgfKSQpqc1sUB0YoSC4heoiDTgrSTdKa8OjbFm5eyGBNQGOt69b4kCq+lGD4r3g+ZtruPx+oUTqtpNvaY35iwb+AX79zCfW1OvviDs7w/sEQEThKc6vcxNjXLfRm2u4+nySmK6Eursb6fGl5+VjIRnuPwj/eKue+H/z947F+hRMxlbk0xOml/u4uZcJQ3L6UvqFqSWWRBthSed4SNb4JCQ9slXPcOixoVjWI3PjwDMwHxpdLxaNID7hL9aK+1C8kiwNYHxHxGvGxxmVDo3qEALS5b1nYmk8a+Qd9w6Jj1/UgqXbJoVMgVm/bdkMETjaoMGaVDVlIhujZnf7D8zaNRmMp+hwyu55EtO0dWZBXzw/EdMq2oSLIge/fqBJdGpnhs9/rpjmnsaqyky+1dLFtr3CNmjBdupPS+CK6bF8mnl+Pbxz3ZjwloeQB8fcICfyl6nhfHFExKdEdRYsYeaS7IfP3iM1tYjMmk8Jc/vZOK0kI+9+QJpmZSL0yO9oygKHBPlgw9AGzFhThtltVZ36tRsQGaCqoKb/49fCP2fvnFF2Hvr4GioKoqXW7vfKxEsuxpqqK0yCzdFtcR8k56KdxvQ83Nws53Bbo9XsosBfPt73VPeZyU5/xLEJmRcsUs0V5r48LwJOFIVAwBb7lXzBJpN0matHRhh2zQ4A6LGvZ6UfyvdidyAVo3K6U5sqtviBvMODMPgLGpWcJRNfszZBrtH4KJyzC0jKGCUTCAqQfAni1VTATn6B1eYY7M3nBjh6znBWFclGQ47tPH3FiLzHxwR90aV2s8OjdWMDo5i2digcPbfEB0XKd+ekKYXyTZHQtHosaICWh5UBx7l5Et9hwSVvdaNlW2cLRmoEM2cEOWZXWZhf/1eCeXR6f4H8+l/p3zcs8wOxsqqLIW6bnKlGlyWLmYckGmGU6loN6Y9sLTPwsv/ldR6P/qq9BwPSbBMzHN+NRsyqMvlgIzd7c4OHJueM0zfRJjIAuyhUTCwr43gd09iMHm7RvKsyOryAbazb3XLeSKVldSvyeJ/rTX2ZiNRLmsZam0f1DclA+fEf/tc4uB8zgDhYmpWYYDM7TV5sAGgr0uthOpz+6f1iFLaY6s+0lhmNL+oRv+eCjbodALaf8goBjfbTE4KiRW5gy65i3B3thc0tuXVrDwjs8imxoTRUaS3ZBAaI4fnLzGozvrsVqy6MKZJnYtN0dWt0OYnsRLpy8cFrEoSf7uXj1vkJiA8gao2SZs7RcSGBIzm9mUK2o4W0VEw/QSUQR64e+/oSAD+ECzg8/dt5Vn3/Xw3ROeZZ64mLHJGbo93qzKFTWaXWWpZ5HNh0MnOUfW/x784z1i3v7BP4XHvyW673GciH2OUu2QARxor+GaL8TZaytsLklyBlmQLWT4jLCSTVBozIQjnL3mzx9DD7ieRTbaKy5UHR/KTv6KhLaamNOiNkfW9gigiC4ZiKK5vOEGI4reIfHY3OiQ6ZtFpgU4J51FNjMJ7/8HbPupRcHaQ9kOhV5ImQs23pEDBVn2QqHjaawqZUNFgjky+wbwx240z78kNgeS7PL84OQ1pucifDLbRUWaaKu1UVxo4kTfgiKgwAL1u26cI+s5JGYGkwxOfvqY2zgxAS0PQt+bi4ud3hfEMRYSn1UyYezh8yzZGf7NAy3ctrmS//bd09c3BhPw2vlRVBX2tWVPrqjR5LDiDc4xPpWCjX+yHTJVhbe/At94SJht/cIh+MBvLOlG3dXnpbjQRNsqnI/vm7e/T0NYtSTjyIJsIdrFpPG2FR929lqAuYhKZ77Mj0HsJlmB9/6PKFqlXDFrNLusFJgU4bQIYKsRQ/XaHJnPs0iuqBVkq/nizzj2enHUyWmxsrSIApPCULIdsrPPiff4zicW/cgQodAL6fiQyIAau5jtlSzP1GhWDT3i2RPLI1tW6lPeEHMqnRI34GU1ULcrqXM/fcxNa03ZfCdpvVFoNrF9Qzld7onFP2y8HQa6RFB9ZA4uJB+crMUEfPzWBmPEBLQ8KLp7F4/c+Oc9h0T2pqsjO+uKZ74gS5P1/eyUCPS2Ly7ICswmvvT4LgrMJj735HvMhBMbJr3cM0y1tYjtG7J/39TsFEqRlObIrE5QTCt3yEI++Pan4dDvQtN98KuvrWgQ1+3xsq2+nEJz6u95p83CzsYKDss8snWBAb71DIbnmLj4Vmxa8WHdsTbzjnxxWASxA1pWA4OnoKRK2ANLsoKlwEyT00pPfJ5S+wfhWreYe1oiFLpnKICtuMAYZhSJ0LlDZjIpuGwWhv1JFmRd34LKLbBu5yXpAAAgAElEQVRx76IfDfpDYp6+zCAdMrguq1yYR2ckguOG6JAB7N1SzdjULBeGl7kZ0z47E1eE7K71oaTMi3oGA3S5vXxydyPKOs5m7Gys4PSAf3GwbuMeEYVyrQv63hI3p0nKFf/9PRET8EmjGKE03AbFFaJDqjE7BZdeFooEI/z9VmwShk7pmiPTvn+XKMgA6itK+ItP7OB0v58/P7RyURiJ2d3f2+Y0xJjHqpwWTWZxD7Rch2ygS7gonv0+3P9H8KmnVpyZnYtEOd3vW5VcUeNAu4sut5fRyVXEukgMhSzIFuJ+W3wRJxEI7bRZqDPSLnkm0GSL7Y+Aef3NR+QS7bX2G7Xj2k35+98VhhgLO2SDk7TV2HLjRrGkUsyj6Oi06LQXMxxIQrI4cRWuvAadP7Pk98CwP4SjzLKqHc20UbkJ6nYaW7YYHAOrQQqy2BzZsrJF7Qb05DMwG0g6Q+vpY24KzQofuyWLDoEZYNfGSmbDUc5e89/4g/mA6LdjQdpF0Lw/4flUVeXp41pMgEFmXM0FInj9/I+uB69fOipCo40wPwZijVXN6ZMsagqFFcxsHry5lk9/YDPfeOMyPz6zvHSu2+PFG5xjnwHmx0BEYBSZTVwcXYXT4sIOmarCsa/D1x8QLtSf/iHc9Z8TbuKcuxZgJhylc+PqC7L97S5UFV6WXbKcx0B3FAZgcljsiCZhVNHt8bKzoSI3bm71RLvJ75ByxWzTXmej3zuNPzQn/qC6GZwdcOxr4r8rrhdkqqrSMxTIDbkiiELIXq9rQVaTbIfs5NPiuPOxJX886A8ZZ34sno5HRYdfx/w23VBVYephkA5ZY1UJdeXFvHV5GWMP7Qb0xDeFOU7TvoTnnAlH+O4JDw/cVJN1B7l007mcsUeZS3SW3e+Igmzz3QndisHAMQGtD4n37cAJ8d89z4OlHDZ9ILvrisfZKnLy0oFmbKNJyJfhCwfbuanOzu8+28013/SSjzl6bhiTAve0GEO2bDYpbKouXV0WWXxBNhOA7/wS/PB3YMs9QqK46Y6kTqXJfteSZXtzvZ0au4UjsiDLeWRBFo/mDpWgIPOH5rg4MsXOJFPV1xV1O8QXUtO92V5J3tMeK656F8oWvX3i3+Mki8OBGXzTc7lTkIH+WWR2C0OJOmSqCl3/Ji6sy+QmDflnjCn7bH9UHI0oW5ydhMisYWbIFEVhb1M1b18aW3qOzFYPKKKrt+WeRcYuS/HjM8NMBOd47Lbk8rZymbryYlw2y+KCDMT188JhGLuQtFzxKaPGBDQfABQ4/6IwZ+h5QViXZ9kp9AYcrWIjOZwGyZr2/WtbuSArLjTzt0/sYiYc5bee6iKyRMbf0d4Rdm2spKLUOJsVTU7r6rLINMni4CkhUXz/u3Dgv8MT377B2TgRXW4fjrIiGipXH/GgKAr722t4tXdksYRYklPIgiwe99tgKhTSnxU45REJ9XnlsKjxgd+Cz70n5skkWaW9Vjgtnl1YkGnESRa1WbOccFjUsNdBQM8OWTHe4NzKw+d9b4qbmyXMPDSG/CFcRizInG1Q3WJM2aJBQqHj2bOlitHJWS4utUNeUCRmRSCFoqKP+vJi7tpqjKIznSiKwq6NFZzoW8bYIxzrkiThTBkIzfFDo8YEWKvFCEPvi9D/ruiWGUWuqOFoE+Yj45f0P7ffIzZRChN/3zU7y/iTj2zjncvj/O2RGyWUI4EZTnp83GcAd8V4mpxlXB0LMhdJoZCx1Yn3wTtfha/dL+YK/9P34e7PJzVnGk+Xe4LOxrUrrQ60u5iajfDOch1/SU4gC7J4PMegvjPhl0+3RzP0yMMOmcmU1G6xJP3UlRdjKy6gZzBujqN+13U3zDiZSU5Z3mtokkWdQi9d89b3K+wkn/g3KCqDmz685I9nwhHGp2aN2SFTFCFbvPL69RBmozAfCm2cgizhHJkmW0yiIPNMBHn9wiif2N2I2QCGBZmgs7GSK2NBJhbahmsKE9fNy3aZ4zF8TEDrg8Kk5N1/BlNsrsxIOFrEMR3GHr7+pMPQAT5+awMf27WBLx8+f8Pn6pXeEQDDzI9pNDvLCEdV3OPB5J+kZZE9/19E3Mivvg6bUzc4800LpdVaDD007tzqwFJg4rC0v89pZEGmEZ4VIX4Ny9uTanS7vWyuLjVU612SfyiKQketnXPxxh6KAjs/JUJN47qY5wYDOG2W3JptsW8QMrfgCnlRKaB1tZYMh45G4eU/g65/he0/DUXWJc+hFXOGnCEDYX+vRq5nJRmFYKxDloKcJ91sqi6lxm7h7eV2let3iRmoJG5In31XZJb99K3r28wjnvk5Ms8C2aKrQ3Tnd3wyqfMYPiag5SFx7Po32HQnlBhsnVpBNpKGgsw/APbU3tN//NFtbKq28p+f6prP+DraM4zTZuHmerv+a1wDq3JarNsp5krv+wP42e9A2eq6fnoqrUqKzHyguZrDZ4eXj/KQGB5ZkGkMnoLIzIp5ERrdbl9+yhUlhqOt1kbPYODGL+H7/gB+5dUbHtc7FKAtl7pjcD2EU6c5MpdtmXDomUn49s/DK38unBUP/vmy59BcGmuM2CEDqL9FFLJGky1qRfUKFtCZRpsje2u5ObJH/hJ+/nsJzxOJqnz7uIe7tjporMof9cCOhnJMCosDok1m+K1uuPO3Ep4jJ2ICardf/y5qeyS7a1mKIqsogNPRIfN7Ehp6LKTMUsDffmoX41Oz/O63u5mLRHm1d4R9rU7D/R03O2JZZKk4LdbthD8YhHt/L6l8veXQDD30ik7a31FD33hwaQm2JCeQBZnGfCD0ygXZkD/EoD+0JlcciUQv2utsBGbC9HvjnK1Mphu07NGoSu9QILfkiqB7FlnNUh2yiavwjYfg3A/hof8XPvJ3K85HDvq0DplBCzJNtnjhsCg0jcL8DJlxOmQAe7ZUMxKY4fLoEjcxipLUDdcbF0bp904bJz8rQ1gtBbTW2JY29jCZk8rpyomYAEURRh6Q1ExcVnC06F+QzUyKHLkUJIsa2zaU818faefwuWF+55lu/KEw97UbS64IUF5aSLW1KHWnRR0Kyy63l2anlfISfQxi9sd+v0ekbDFnkQWZhvttscuUYDdIC4Te2ZiH82MSw6E5Ld4QEL0A90SQ0FyUtlqD5Pski/ZZ1LJw1khVaREFJoUhrUN25XX46n3gc8PPPAt3/HrCC632XEPOkGm0f0h0+y/8ONsruU5wTBgmWYy1KbCnSXTs3rq0+pm7p4+7qSgt5MGba/RaVs6wa2MF3W4v0SVc9RKhxQQ8eFOt8aXU9/4+fPzrULk52ytZGkebyCKL6uiylyAUOhGf/sBm7u9w8f3uAcwmhTsNanYjnBYz21VSVZUunZVWGypK6Kizc/istL/PVWRBpuE5lpRc8aTHh9mkcHO9LMgk2Ufrep1boSDLSYdFEJlGilm3DpnJpOC0WUSH7Pg34F8+IkwmPvMybD2Q1DmG/CGKCkxUlBrI9nohG+8Q/19Gki0Gx8T8mMEkS00OK06bhbcvr25OcXxqlh+9P8RP7dqApWD18qVcpbOxAt/0HJfHUr+h/dGZISaCc8Y184invAG2fyLbq1geRwvMTenqSotfzEWutiBTFIW/+MRO6sqL2bOlSrdOkN40OcpSkyzqQL93mtHJGd3nJg+0uzh+dQJfcE7X80oygyzIAHwesQufjKGHx0t7rY3iwvy7+EqMh624kMaqEs5e8y/7GM1hsSXXCjKT+cbMFx2oKzPz8JX/CT/4bWjeD7/8YxGonSRDsVBoo81C3IC5QMy69L6Ynmyi1RAcM5TDooaiKOzZUrX8HFkCvnuin9lIlMdyoahIA7s2VgLQtXCOLAmePubOm5iAtONsE0c9A6K1jbBVSBY1Kq1FfP9zd/F3T9yi06L0p8lpZXRyNqNFjCbz7Wys1PW8+ztcRKIqr5wf0fW8kswgCzKIC4ReuSBTVZVut1e3IUyJRA/aauwrShZ7hiZpqCyhzGgZP8lgr9dNssjUGH829d+5f+oHwnDgU09BcWqd7kF/yNhyRY2OD8NsAC6/mvixmcCgBRkI+/sh/wxXx1KwvkZcD5455mZnQ/l8JmC+0ewso8xSsPQc2QrkY0xAWnG0iuPo+ZUflwq+2PeubW1h3Y4yC5UGlqQ2OYWU/2IGu2RdfV6KCky01eq7SbqzoYJqaxGHz8o5slxEFmQgCrKCEuGmtAJXxoL4Q2E65fyYxEB01Nm4NDq1bOBx72AOOixqaFlka2XoffjqPppnzvIHyufggT9elUPWsH/GmKHQC2m6F4pscPa5bK9EMDVq4IJMmyNLTbbY7fHRMxTgsdsSZ22tV8wmhR0N5ZxwLxEQvQLfPp5/MQFpxeoUm0ujenbI+sHqWtHkaD3QvBrr+zXS7fGyrd5OUYG+t+Bmk8K+NhdHe0YIpxJ2LTEEsiADYeix4RYwr6xx1gw9ZIdMYiTaam1EoioXhhfv8M2Go1wcmaRV5524jGGrB/8aJYtnfwBfewDCs/z7zq/wb9N3LFu8roSqqrnTISuwiEDbc89DNPX/V93RZsgMSLOzDEdZ0fJ5ZMvw9LE+SgrNPLpzbR2EXGfXxgrOXQsQmkvufRaJqjz7bv7FBKQVRblu7KEX/v6ULe9zkcaqUgpMCpdGMtMhm4tEOdXv012uqHGgw4Vveo73ViEjlmQXWZDNTcPgyaQMPbrcXkoKzbS4csytTrKu0eRSNwREx7gyNkU4quZ2h2w2AKHlZ+SWRVXhlb+Ap38GXO3w2aOo9bcCMLJUOHQCJmfCBGcjxg2FXkjHoyKQue+t7K4jMgchr2E7ZGKObIU8siUIzob5fvc1Htleh63YmGYFmaKzsZJwVOV0vy+px+drTEDacbTqa33vHxBmJuucQrOJjdWlGeuQ9QwGCM1F6dyYno39u1scFJgUDkv7+5xDFmQDJyAaTsrQ46THy/YN5RSY5a9NYhw2V5dSVGCiZ2hxQZazDosa89b3KcoWZ6fg25+Gl78IOx6HTz8P9jpcsWJqeBUFmWZ5b9gMsoVsfQDMluy7LU7H5GwGLchAyBav+UK4x6cTPxj44clrTM6Eefx2WVR0xpziFgVEL0M+xwSkFWcrTA7BtE6dEV9+dMggs06L3Z6YoUealFa24kL2NFVxRNrf5xyyskjS0GMuEuX0gJ8dDXJ+TGIsCswmWmvKlnRa7B0KYDYpNMV08jmHdkOQip2z1y3Cns98Dx74E/ipf4BCUUS5bLFwaC2LLAUMHwq9EEuZcJI89wPRLcwW86HQxi3I9jSJtSU7R/b0MTdNTiu7N6VHdpRLOG0WGipLkjL2GJ+a5aX3B/M2JiCt6GnsMROAGd+qLe9zjWanlStjQSKryNNLla4+L1XWIhqrStL2Gvvbazg/PElfikZFkuwiCzL3O1DVlHC+oWcwwGw4qmuQn0SiF+21Szst9gwG2FxdmrsxDal2yK6+CV/ZBxNX4Yln4M7fvCH7So8OWU7MkGl0fEgEX1/rzt4agrEix8AFWYurjCprEW8lkUd2YXiS41cn+OTuRmPHH2SQzsaKpAqy757oZy6i5m1MQFqZL8h0MPaYt7xf/5JFENb3s+Eo/RPJdcjXQpfbS2djRVq/Ow60uwA4ImWLOUV+F2SqKgw9GvckfOh8m1kWZBID0l5rYzgww9jkjYVG71BAd2vdjKJZLidTkL33L/B/HhVuY798WJhaLKDaasFsUuaLq1QYzDXJIkDLQ4ACvS9kbw3BWIfMoKYecD2P7O1LiY09vn3cTYFJ4WO35Ef3IBk6Gyvo906v2HmejwlorMjbmIC0UrEJzEX6zJH5tFDoPJEsZsj6PhCa48LIJDvTbAy32WGlyWnl8DkpW8wl8rsgm7gsbhaSMPTodnupLC2koTJ9bWaJZLVoNzjxXbLp2QhXx4O5Oz8Gwi3Q6ly5IIuE4fnfg+c+B1vuhs8cFvMUS2A2KTjKihj2p94hG/aHsBcXUFKUQ93GMqf4fut5PntryIEOGYg8sn7vNO7x5WU+c5Eo33nPw/5217z8VXI9IPrECl2yLrdXxARIM4/0YC6AqmYY0aEg075v80Sy2OTIjPX9KY8PVSVthh7x3N9Rw9uXxpmcCaf9tST6kN8FmTY/lpShh4+daW4zSySrReuCnYsryC4MT6Kq5K7DooatbvmCLDgO//oxeOcf4Y7fgCe+DSUrz/XU2ItXJVkc9Idyqzum0fqwkCz6dArYTpVgrOtk8IJsTxJ5ZIfPDjM6OSsldwu4ud5OoVlZUbb4zHG3jAlIN06dnBb9/YCy5lDoXKHKWkR5SSEX02x9r21Y7MyAF8H+dhezkSivnx9N+2tJ9EEWZEU2cHWs+LCpmTC9Q4G0t5klktXitFlwlBVxbvC6sYfmupizGWQa9g1LF2TD5+Cr+6HvTfjI38NDfyp2iRPgsllWJVkc8s9QW56DBVnbI+KYLdni1ChYyhPmPGabVpeNytLCFfPInjnuxmWzcG+rM4MrMz7FhWY66uyc6Fs6IHpqJsxzXQMyJiDdOFph4gqEU99wugF/P5S5oKBIl2UZHUVRaHZa055F1uX2ssVhpaI0/b/XWzdVYi8ukHNkOYQsyBpuBdPKEqTT/T6iKuxslA6LEuPSVmu7QbLYOxSgqMDEplwPX7XXx3Zs4+g5BF+7X9jbf/qHsOtnkj6dy168qhyyIX8oN2Vqzjao3Jy9giw4BlZjd8cATCaF27dULdshG/SFONozzE/vbpDRJ0uwq7GCUx7fkk51Pzx1janZiIwJSDeONlAjMH5pbefx9eeNXFGjyVmWVsmiqqrzhh6ZoNBs4t42F0fOjRDNgHukZO3k71VlJgDD7ydl6HHSIwIvd8gOmcTAtNfa6RkKzN8Q9QwG2Oosy/2bR3sdTI/DXEgY8bz21/Dkp6C6GT57NKkZ0HhcNgtjU7PMhqNJPycaVRkOzFBbniOh0PEoiuiSXXpFFLCZJjhqeLmixt6majwT03gmFs+RPfuum6iKDDRehs6NFUzNRjg/vNjt9RkZE5AZHC3iuFbZoj9/Msg0mpxWhgMzBEJzaTn/NV+IkcBMRo3hDrS7GJ2c4WSSoe2S7JLjd2proP9dUKNJ3cx1ebw0VJbgKMvBmzFJ3tBWayM0F6UvZkqQ8w6LGtpO7fgl+M4vw+E/gm0fg184BOWp7+Jqc2Cjk8l3yUanZohE1dycIQMxRxaZgYsvZ/61g2NQalyHxXj2bBGF40K3xWhU5ZnjHvY2VbGpOkcz/dJMZ2PM2GNBQLSMCcggWkG2VmMP/0DeWN5rNDmE0+Ll0fRsWmnzlZksyO5tdWJS4MhZKVvMBfK3INMMPTbsTvjQbrdXzo9JDE9HzGnx3DU/vuk5rvlCue2wqKHt1H7zo3D6O3Dgf8DHvw5Fq5NiumxiYyWVOTLNlTFnC7JNHxBzXL2HMv/aU2M50yFrr7VRXlLI2wvyyN66PEbfeJDHb9uYpZUZn83VpVSUFtK1oCCTMQEZpMgK5Y1r65CF/DDjz7sOWbMzvU6L3W4vRWYT7XWZuyZXWou4dVOltL/PEfK7IHN2QMnKhdbY5AyeiWk5PyYxPC01ZZgU4bR4Pmbo0VZbluVV6YDWIZudgk89CXf/zg1hz6miFVWpOC0O+nIwgywecyG03A+9L0I0eanmmlHVWIesKnOvuQauz5Hd2CF7+pgbW3EBD2+rzdLKjI+iKIsComVMQBZwtKwtHDrPLO81NlaXYlJIm7HHCbeXm+rtWAoyG5uyv72G9wf889cwiXHJz4IsGgXPO9B4W8KHyvkxSa5QXGhms8PKuUH/dYfF9dAhq94KD/+5CHtuO7jm02kdspVCbBcyFBCPrc3Vggyg9SBMjQi5dqaYnRRSSQOHQi9kb1M1feNBBrzTAPiCcxw6PchHOzdQXJhDGXRZoLOxgt7hwPwcjowJyAKONhg9v/qNF78WCp1fBZmlwExjVSkX0yBZDEeinPL4MipX1DjQ4QLgiOySGZ78LMjGzkPIl5ShR5fbi0mB7Rtkh0xifDpq7ZwbDNA7GMBaZGZDxToIMlcU2Pur4GrX5XTVZRZMSmodsiFfCJMCjrIctoFuuR8Uc2ZDonMkFDqePVtEN0+TLX6vu5/ZcFQWFUmwa2MlqioCcEHEBNTYZUxARnG0wFwQAstkNyZCyytcxXxurtPksHJxWP8O2fnhSabnIlkpyFpcZTRUlkj7+xwgPwuymQBsuDVJh0UvLS4bVkvifCOJJNu01droGw9ywu2ltdYmh+iXwGxScJSllkU25J/BUWbJbcfKkkoxS5ZJ+/sprSDLnQ5ZR50de3HBvLHHU++4ubnezja5KZeQzpiS5ITbOx8T8IlbZUxARnG2iePIKmWL/gHyKRQ6nmZnGVfGpnS3ic+GoYeGoigcaHfx+oVRQnORjL++JHny81uyYTd85sh1R6JlUFWVbo+PHRlIVZdI9KC91oaqCqlt23qQK6aJGntxajNk/lDuzo/F03YQhs+I8NhMkIMdMnNcHtnpfh9nrvlldyxJyksLaXJYOdHnlTEB2cLRKo6j51f3fL8HymoMH+SeDpqcZYTmogz4pnU9b1efl4rSQjZVZycT9EBHDaG5KG9eXDpjUWIM8rMgSxLPxDTjU7PszMKuhkSyGtpjTouwTubH0oTLZmHIn4Jkcb0UZK0Pi2NPhrpkWkGWA8HQ8extqubKWJAvHz5PUYGJj+zMP/nWauncKIw9ZExAlrA6obhi9cYe/oG8lCuCyCID/Z0Wu2JO3dlSrOxpqqK0yMxhKVs0NLIgW4FuT/bazBLJamioLMFaJIwH1kUGWZpw2YsZCaQiWQxRY18HOYTVzWLoP1NzZMFRccyhDhlczyN76cwQj2yrpbw0/7oFq2VXYwWjkzMyJiBbKIrokq22Q+bLv1BojesFmX5zZJMzYXqHA1m9j7QUmLm7xcGRs8Ooqr5yTIl+yIJsBbrdXooKTPLGVpIzmEzK/PtVdsiWx2WzMDo5y1wksRPZTDjCRHAutx0W42l7GK6+IYyN0k1wDEyFYLEnfqyBuKneji02N/xJKVdMCS0gWsYEZBFH69pmyOz5FQqt4SyzYLMUcElHp8VTHh+qKjrH2eRAew0DvhDnBgNZXYdkeWRBtgLdHh8319splAPJkhxi18ZKNlSU5LYjYJrR5Iejk4lli/Oh0OXrpSB7BKJhuPDj9L/W1KjojuWYuYzZpHBXi4Mmp5W9W3Kru5dt2utEuPYnbm2QMQHZwtkKU8MwPZHa80I+mA3krWRRURSanFZdJYvzhh5Zjk7a1y6cTqX9vXGRlcYyaLkRO2X+mCTH+N2H2vjeb9wpHRZXQMsiS2aOTHNjXBczZAANt4kiKRNzZMHxnJMravzPT+zgO7/6AUwm+TlKhUKziZd++x6+cFCfmArJKpg39riQ2vM0y/s8lSyCMPbQU7LY7fayqbqUSmt2N0hdtmJ2NpRz+KycIzMqsiBbhgsjIjdiZ6N0WJTkFsWFZhxl62DeKY1oxVUy4dCD/nUQCh2PyQwtD8L5lyASTu9rBUdzztBDw1ZcmPWbqFylxl6MpUB2x7LGfEGWomzRH8suy1PJIogssgFfiOCsPt+NXW6vYXwI9rfXcMLtTUoZIsk8siBbhpNuMV8hO2QSyfrDFTPoGErC+n7Qp3XI1lGR23YQQl5wv5Xe1wmO5WyHTCLJWSo2gbkIRntTe57fI4553iEDfZwWB30hBv0hwxRkBzpcqCoc7RnJ9lIkSyALsmXo8nixFxewWVr2SiTrjmprESYFRpLokA0HZrAUmCgvWUdOe837xQ1bz6H0vs7UaE6FQksk6wJzAVQ1w0iqBdkAKCaw5a8ZS7Mr5rSog7GHNj9mlOikm+vt1NgtHJH294ZEFmTLcNLjZUdDhZwfkEjWIQVmE9VlyWWRDfpEBtm6msmz2GDz3ektyCJh0YWTHTKJJPM4W1PvkPn68zYUWmNztRVF0cf6vsvtpdCscFOdMVxmFUVhf7uLV3tHmQ0ndhjWk9lwlK+9dom/+VGK78k8QhZkSxCai3DuWkDOj0kk6xiXzcJwEllkQ/7Q+pkfi6ftIIxfXH1eUSKmx8XRKjtkEknGcbTCxGUIpzAv5PeAPT8dFjWKC81sqCjRRbLY5Z7gpjq7odxG97fXMDkT5tiV8Yy95iu9Izz8pVf54g/P8qXD5zkZy/iV3IgsyJbg/QE/4ajKDjk/JpGsW2rsxUm7LLrW0/yYRuvD4piukOjgmDiWVqXn/BKJZHkcbaBGYfxS8s/xD+St5X08Tc4yLo2urUMWiarCqdsgckWNu7Y6sBSYOHw2/fb3fWNBPvMvx/lP33iHaFTlfz+xC5ulgK++djntr52LyIJsCbTq3SiDmBKJRH9Eh2zlgkxVVYb8M+uzQ1bRCDXb02d/P1+QyQ6ZRJJxHC3imKxsUVWFZDHPO2QgnBYvj0yhquqqz3FheJKp2Yjh7iNLisx8oLmaw+eG1vT/txLTsxH+6qUe7v+bV3jjwii/93AbL/72PXxoRz1P7NnI86eu4R4PpuW1cxlZkC1Bt9tLrb14/eQOSSSSRbjsxYxNzRCOLK+l94fCTM9F1u93QdtB4bQYTIN8ZWpUHOUMmUSSebSCLFljj5AP5qZkQQY0O61MzUaSUlAsR5dbhHIbrSAD2N9Rw9WxoC7GJfGoqsoPTg5w4K+O8rdHLnBwWy1HPr+PX9+3dT4G49N3bkYB/umNK7q+9npAFmRL0O3xsaNBzo9JJOsZl82CqsLo5Oyyj9FyymrK12tB9rCQNZ1/Sf9zax0yOUMmkWSeIiuUNybfIfPLUGiN69b3q5ctdrmFU/cWh/Gcuve3uwA4oqNssWcwwBNffZvf+NYJykuLeOZX7uBLj++idsG1s668hA/vrOfpY334pud0e/31gCzIFuALznF5dMpwul+JRKIv8+HQKxh7aKHQNbZ1OEMGUK4Z9joAABoHSURBVLcLymrT47aoFWQlcoZMIskKjpbkw6G1UOjy/A2F1mhyiiLq4poKMjE/ZkR33g0VJbTX2jisg/29LzjH//Pc+zzy5dc4O+jnTz66jR987i5u37L89/4v393E1GyEJ9/pW/PrrydkQbaAk/1yfkwiyQdcsSJrJVmK9rOFu3zrBpMJWh+CC4chvHyncFUEx8Bih4Iifc8rkUiSw9EmXFSjSVic+7RQaClZrLUXU1pk5uIqnRaDs2F6Bv3sMvB95IEOF8euTKy6SxWJqjz1Th/3/dVR/uXNK3zq9kZe/vw+fm7vJswJ4qJuqrdz11YH//TG5Yzb7xsZWZAtoDsW5Ldtg5QsSiTrmWQ6ZENah2y9zpABtD0CswG4+rq+550alfNjEkk2cbTAXBACA4kf6+8XodBlNelfl8FRFIUmp3XVM1anPD6iKnRuNG5Btr+9hkhU5dXekZSf+17fBB/9uzf4wr+fotlp5bnfuIsvfnQ7ldbkN98+c08TQ/4Zvt+dxHszT5AF2QK6PT6anFbKS/I3GFEiyQccZUUoSqIOWYjykkJD5cjoTtO9UFCiv2wxOCYLMokkmzjbxHEkCdmifwBsdWAuSO+acoQmR9mqZ8i6Y07dOw0cndTZWEGVtYjDZ5OXLQ4HQnz+mW4+9vc/YTgQ4kuPd/LMr9yxqgbGPS0O2mpsfPW1S2lze8w1ZEG2gG63l04Df4gkEok+FJhNVFstjKw0Q+YLUbMeM8jiKSyBpn3C/l7PC2NwVBp6SCTZxNEqjsmEv/s80tAjjianlX7vNKG5SMrP7XJ7aawqobrMuNcOs0lhX5uTo70jKzoNA8yGo3z11Uvs/8tXeK67n1/b18yRz+/jI50bVj0jpygKn7mniXODAV47P7qqc6w3ZEEWx6AvxHBgRjosSiR5gstmWblDFphZ33JFjbaD4OuDoff1O2dwXHbIJJJsYnVCcUVyxh7+ATk/FkeTswxVhStjqcsWu/q8dDZWpmFV+nKgvQZvcI4TsVGdpXi1d4SDX3qVP33+LLdtruSl376X33+4Hatl7Z3UD++sp8Zu4auvpRBevo6RBVkcXbE3pXRYlEjygxq7ZeUZMl8oPwqy1ofEsVcn2aKqSsmiRJJtFEV0yRJ1yFRVzJDJgmyepphd/aUUjT2G/SEGfCF25sDG/t2tDgpMCoeXsL93jwf57L8c5+e/8Q6RqMo3Pr2bf/qF23W18S8qMPHpD2zhtfOjnBnw63beXEUWZHF0e7wUmhU66uzZXopEIskALlvxsh2ySFRlZHKG2nwoyGy1sOFW/ebIZqcgHJIFmUSSbRytiWfIpieE+Ue5LMg0NOv7VOfItI39XQY29NCwFxeyp6mKI3H299OzEf76pR4O/PUrvH5hlN97uI0Xf/se9renx+zliT0bsRaZ+ZrsksmCLJ6THi/ttfb1PcAvkUjmqbFbGJucWVJDPzY5QySqrv8ZMo3Wg9D/LgTWnk0jQ6ElEoPgbIWpYVF0LYeWQSY7ZPOUFhVQV16csvV9l9tLgUnh5nrjd8hAuC32Dk3iHg/y/Klr3P/Xr/DlIxc4uK2WI5/fx6/v24qlIH33xOUlhTx220ae6x7gmm86ba+TC8iCLEY0qnLS7WNnY258iCQSydpx2ouJqjA2tTiDS+uc5YVkEcQcGUDvC2s/VzA2pC07ZBJJdpk39riw/GP8/eIoC7IbaHam7rTY5fbSUZc7G/sH2l0A/PQ/vMmv/9t72EsKeeZX7uBLj+/KWP7mL9y5GRX45zeuZOT1jIosyGJcGp0iMBNmh3RYlEjyhppYOPTwErLFwVgG2boNhV5Izc1Q3qhTQTYujrIgk0iyy3xBtoJsUSvIpGTxBpqcVi6NTCVtyx6Nqpz05NbG/maHlY46O6FwhD/56DZ+8Lm7uH1LVUbX0FhVyiPb6/jW230EQqsLql4PyIIsxslYbkSnNPSQSPIGV6z7pQVAx5MXodDxKIrokl18GebWKB2Zkh0yicQQVGwCcxGM9i7/GF8/KGYZCr2AJoeVwEyYkcnlnXjjuTgyyeRMOCccFuN56jN7ef339/NzezdhNq3Oxn6tfObuLQRmwjx9zJ2V1zcCsiCL0e32Yi0y0+wsy/ZSJBJJhtDmw4YDiy+4Q/4QJgUcBs6S0Z3WhyE8DZdeWdt5tBkyWZBJJNnFXADVW2FkhYJMC4U25YbMLlM0xe4Hk3Va1Ozjc21jv7y0kDIdbOzXwo6GCvY2VfGN1y8zlyAXbb0iC7IYXR4f2zaUZ213QCKRZB5HmQVFWbpDNugL4bRZ8us7YfNdUGRbu/19cBRMBVCcO9IdiWTd4mhZuUPml6HQS3HdaTG5gqzb7cVWXDBvmS9Jjc/e08SAL8Tzp65leylZQRZkiBTyswP+nNvVkEgka6PQbKLaWrR0hyyQJ5b38RRYYOt+6HkBomvYpdQyyJQ8KmYlEqPiaIWJyxBeRnrn65fzY0tQX15CcaEpaWOPLreXnQ0VmPJpE09H9rW62Ooq4yuvXkp6bm89IQsy4Nygn9lIVAZCSyR5iNNWzPBSM2S+0PyMWV7RehAmB+Fa1+rPMTUGpdLyXiIxBI42UKMwvkTWk6oKyaJ0WFyEyaSwudrKpdHEHbLp2QjnBgNyY38NmEwKn7l7C+8P+Hnz4li2l5NxZEEGdHt8AOzIgWR1iUSiLzV2yzIdslD+dcgAWh4ExbS2kOjgGJRm1qlLIpEsg6NFHJeSLU5PiLlRWZAtSbOzjItJdMhOD/iIRFW5sb9GPtK5AUeZha/kYVC0LMgQul9HWREbKkqyvRSJRJJhXDbLohmy0FwEb3Auf0Kh47FWQ+Oetc2RBcdkKLREYhS0gmwpYw9peb8iTU4r7vEgM+HIio/rzlFDD6NRXGjm0x/YxNGeEXoGA9leTkaRBRnig7SzoQJFzjtIJHlHjb2Y0ckZItHrmvXhfAuFXkjbQRg8Bd5VWhAHR6XDokRiFIqsImNwqQ6ZT4ZCr0Szs4yoCn1jwRUfd8LtZUNFCU5bHm7i6czP7NlESaGZr+VZlyypgkxRlBpFUU4oilKgKEqfoihHY/9sT/cC083kTJgLI5MyEFoiyVNcNgtRFcbismYG8y2DbCGtB8VxNSHRkTBMe+UMmURiJBytS4dD+2VBthKa0+LFBE6LXX1eOjfK+0g9qLQW8cndDfxHV/+S893rlWQ7ZH8JlAA7gCdVVd0X++dU+paWGU55fKgqOZWsLpFI9MNpE0VX/ByZJmGsLc/TgszRAlXNqyvIpicAVXbIJBIj4WiF0fOL3VP9/SKiosyVnXUZnC0xC/tLo8vPkY0EZuj3TtMpN/Z14xfv2kIkqvLPP7mS7aVkjIQFmaIo+4EpYBDYC3xIUZR3FEX5uqIo2U2S04Fuj9D97pQfJIkkL9HmxOLnyLR/r7HlaUGmKEK2ePlVmElRxz8fCi1NPSQSw+Bogbng9Y6Yhq9fhkKvgK24EJfNsmIW2fz8mOyQ6camaisP3VzLv751lamZcLaXkxFWLMgURSkC/hD4QuyPjgH3q6p6O1AIPLLM8z6rKMpxRVGOj4yM6Lle3Tnp8bKxqpRKa1G2lyKRSLKAZm2/sENWXGjCXpLze06rp+0gRGbh4supPS84Ko7S1EMiMQ7ONnFcOEfm75dyxQQ0Oa0rZpF1ub2YTQrb6qXSSk8+c08T/lCYZ46vcpY5x0jUIfsC8Peqqnpj/31SVVUtQvs40LLUk1RV/YqqqrtVVd3tdDp1Wmp66Hb7pE2pRJLHOMtEh0wz8gAY9M9QYy/Ob6Ofxr1QXJG6/f18h0xKFiUSw+BoFcfR8zf+ub8f7PWZX08O0eQsWzGLrNvjpa3GRkmR7DLqyS0bK9m9qZKvv36ZcCSa+Ak5TqKC7H7g/1IU5SjQCRxSFGWnoihm4KNAd5rXl1Y03e9OmT8mkeQtRQUmqqxFDAVulCzmraGHhrlAZJKdfxGiK1s+38BUrEMmTT0kEuNgdYoNlnhjDy0UWlrer0iTw4o3OMf41Oyin0WjKl1uaeiRLj5zTxOeiWleeH8w20tJOysWZKqq3qMZeABdwG8C34z9+5uqqv44/UtMHye1+THZIZNI8hqXzXJDh0wWZDHaHhYdL8+x5J8THBdHOUMmkRgHRblu7KERHIdwSEoWE9DsLANYMiD60ugUgVBY5o+lifs7atjisPLVVy+hqmriJ+QwSeeQxQqz06qq7lBVdbuqqn+QzoVlgu6Y7vfmenu2lyKRSLKIy17McKxDpqoqQ/4QtfkYCr2QrfcLB7ZUZIvBUbDYoUD+/iQSQ+FohZG4DpnfI46yIFsRrSBbao6sSwZCpxWzSeGX7tpCt8fHO5fHs72ctJLXwdDdHh8trjJKi/J4cF8ikVAT1yHzT4cJzUVlhwyguBw23ZliQTYmu2MSiRFxtsLUcCyaAiFXBClZTMCGyhKKCkxLOi12u72UWQrmizaJ/nz8lgaqrEV89bXL2V5KWsnbgkxVVbo9XrmrIZFIcNktjEzOEImq87NksiCL0XZQzJ2MXUzu8cExOT8mkRiRhcYePtkhSwazSWFzdemS4dBdbi87Gsoxm/LYACrNlBSZ+bm9m/jx2aElZaPrhbwtyPrGg3iDc3J+TCKRUGMvJhJVGZ+aZdAnC7IbaH1YHJMNiZ4alQ6LEokRmS/IYtb3/gEhSbbKUOhENDnKFoVDh+YinL3mlxv7GeDn7tiEpcDE19ZxlyxvC7Jujw+AHdJhUSLJe1y26+HQWih0rSzIBFVbwNmRvGwxOC4zyCQSI1KxCcxFcQVZP9jqwZS3t4JJ0+S00jcWZC7Ofv39AT/hqCo39jOAo8zCx29t4DvveRidnEn8hBwkbz+F3W4vxYUmWmts2V6KRCLJMlo49EhgZr4gc0lTj+u0HYSrP7k+e7IcqipMPeQMmURiPMwFUL0VRuI6ZHJ+LCmanGWEoyru8eD8n2mGHrtkQZYRfumuLcxFovzLm1ezvZS0kNcF2bb6cgrNefsrkEgkMW7skM1QUVpIcaEM+Zyn7SCoEbhweOXHzQWFjbaULEokxsTRcr1D5vPI+bEkaXJaAW4w9uhye6kvL57f0JOkl2ZnGfd31PDNN68wPZtCNmaOkJfVSDgS5fSAjx0NcldDIpGAM1aQDQdmGPSHpFxxIRtuFcGyiWSLMhRaIjE2jlaYuAxzIdEhs9dne0U5QbNjcRZZt9sr5YoZ5rP3NDERnOPZ9zzZXoru5GVB1js0SWguys5GOT8mkUjAUmCmsrRwfoZM7nguwGSGlofg/I8g8v+3d/exVdV3HMc/3z7TB1oe2spTkSKtTBHYmKJCBUcm3ZIlizr3kM1o0MVEE//Y5pJlWVyy/TGzv/aHiwwXsyU+zGRZTHxahg6YUyND43TCWOUZBQot0AIt7W9/nHPopdyL9/a293d6z/v1z73n3Fv6Df311/O5v/P7/QYzv6+/O3hkhAyIp5ntkhsONnsfOifVz/Vd0aRQX12uGTUVF0bIuk+f077j/SzoUWAr5k/TsnkN2rS1S0PDxbVRdCIDmZPTusXN+nzLNN+lAIiJ5qlVOhLOIWNT6DTaO6VzvdK+f2Z+TxTIWNQDiKeZi4LHrteCR0bIsrawcWSlxfcOsCG0D2am+ztatae7X3/98FPf5YyrRAaya2bX63d3r9C86dW+SwEQE411lTrce0ZHT51jyft0Fq6VSisvf9siI2RAvEWB7H9RIGMOWbZaG2sujJC9u69HJSYtYaXugrvtmis0b/oUbdza5buUcZXIQAYAozVPrdKuT09r2LEHWVoVNVLrLUEgcxluFSGQAfFWUSPVz5MO7QiOCWRZa22sUXffgHr7B/XugV61NdepuqLMd1mJU1pi2rCqVdv3ntD2vcd9lzNuCGQAoGClxYHzwR4zBLIM2tYHCwIc3Zn+9b5jwUazVXxqDMTWzDZJTiopDxbrQVZaw4U9dh89rff292h5C7cr+nLnirmqn1KujVuKZ6NoAhkA6OIQxiqLGbStDx53Zbhtsb87GB0zK1xNAHIzsy14nMqm0LmIlr5/7aMj6j0zyPwxj6oryvTdlfP1yoefaM+xvs/+gkmA30QA0MheZJLUzKIe6dXPkWYtzTyPLApkAOIrmkfG7Yo5mTe9WmUlpj/vOChJLHnv2fdumq/ykhJt2lYco2QEMgCQLix1X1pimlFLIMuorVPa//bInmOpCGRA/DW2B4/1BLJclJeWqGVGtQ72nFFNRakWNdX5LinRmuqq9PXlc/Sn7ft1vG/Adzl5I5ABgEZGyBprK1Vawi13GbV3SnLSf1+99LW+YwQyIO5Sb1lETqJ5ZEvm1vN3IgY2rF6gs4PD+uObe32XkjcCGQBIagpvU2yuZ/7YZc1aKtXNlna+eOlrjJAB8VfTKK17VFr2Hd+VTDoLm4J5ZNyuGA+Lmuu0tr1RT72xR2cHh3yXkxcCGQBIqiwrVUN1uZrruF3xssyk9vXS7s3S4NmR88ND0pkTbAoNxJ2ZtOrhkVsXkbWF4QjZcgJZbNzX0aruvoELc/smKwIZAIQeXHuVvnV9i+8y4q+tUxrsk/ZsGzl35oQkxwgZgKK19uom3fmFuVq1iO0C4uLG1hm6ds5UbdzapeHhDHtkTgIEMgAIbVjdqrVXN/kuI/4WdEjl1Rcvfx8t8kEgA1CkGusq9didS1VbyYbQcWFmum91q7qO9mnzR0d8lzNmBDIAQG7Kq6SFt0o7X5Zc+Ilkf3fwSCADABTQV5bM0pyGKXpia5fvUsaMQAYAyF17p3TygPTJ+8FxFMiYQwYAKKDy0hLdc/OVevvj43p3f4/vcsaEQAYAyN2i2yTZyCbR/dyyCADw45vXt6iuqkwbJ+koGYEMAJC72kZp7oqReWTcsggA8KS2skzfvqFFL71/WPuP9/suJ2cEMgDA2LR3Sod2SCcPS33dUkWdVMa2AQCAwrvnpgUqMdOmbR/7LiVnBDIAwNi0dQaPu14ON4We7rceAEBiXVFfpa8tm63n3tmvnv4B3+XkhHU7AQBj07RYapgfBLKhARb0AAB4dd/qVh3uOasT/YNqqK7wXU7WGCEDAIyNWXDbYtfrUu8B5o8BALxaPGuqnr5/pRbMrPFdSk4IZACAsWvvlM6flY7tkqoZIQMAIFcEMgDA2LXcJFVODZ4zhwwAgJwRyAAAY1dWIV21LnjOHDIAAHJGIAMA5Kc9XG2ROWQAAOSMQAYAyE97p3Tt7dKCDt+VAAAw6bDsPQAgP5V10h1P+q4CAIBJiREyAAAAAPCEQAYAAAAAnhDIAAAAAMATAhkAAAAAeEIgAwAAAABPCGQAAAAA4AmBDAAAAAA8IZABAAAAgCcEMgAAAADwhEAGAAAAAJ4QyAAAAADAEwIZAAAAAHhCIAMAAAAATwhkAAAAAOAJgQwAAAAAPCGQAQAAAIAnBDIAAAAA8IRABgAAAACemHNuYr+B2VFJeyf0m4zNTEnHfBeB2KA9IEJbQIS2gAhtARHaAlLl0h7mO+ca070w4YEsrszsHefcCt91IB5oD4jQFhChLSBCW0CEtoBU49UeuGURAAAAADwhkAEAAACAJ0kOZE/4LgCxQntAhLaACG0BEdoCIrQFpBqX9pDYOWQAAAAA4FuSR8gAAAAAwCsCGQAg0cys2cy2phwvNrO/pByvMrPdZva6mf3NT5UACi21bzCzlrAP2GxmT1hgjpkdCM+/bmZplzRH8TGzWWa2zszqxuPfS0QgG/ULVW5mL5jZP8zs3kznUJyyaAt0rgmRxUV4g5ltCdtHp58qMdHMbJqkpyTVhMcLJT0mqT7lbddLesg5t8Y596XCV4lCyuIinGuGBBjdN0j6vqQHnHO3SponaYmkGyT9Iuwb1jjnjvqpFhNtVL/QJulZSTdL+ruZVeTbLxR9IEvzC/WQpO3OuZsl3REm23TnUGSybAt0rgmQ5UX4zyU9KalD0o/MzApdJwpiSNJdkk6Gx6ck3T7qPSsl/dTMdpjZg4UsDoWV5UU41wzJcFHf4Jz7iXPuP+FrMxRsBrxS0gYz+5eZ/dJPmZhoafqF6yTd45x7VFKXpAXKs18o+kCmS//YrpH0XPh8i6QVGc6h+GTTFuhckyGbi/AOSc8754Yk7ZR0ZcGqQ8E4504653pTjo84586NetvvFbSHGyU9YGYzClkjCiqbi/A14pqh6I3uGyJmdpekD5xzhyS9pKA9fFHSjWZ2XWGrRIGM7heel7TXzL4qaZqk3cqzXyj6QJbmF6pG0sHw+XFJzRnOochk2RboXBMgy4vw88650+Fz+oVk2+ycO++cOyvCeVHL8iKca4aEMrNWST+Q9HB46g3n3Knwg7sdkhZ5Kw4TJkO/UCvpG5L2SnLKs18o+kCWxmlJU8LntQr+D9KdQ/FL93Onc0VkKOU5/UJChbeqbjOzWjNrlrRcwaehSIg0F+FcMyRQeNva05LuTbk4fyVc3KFa0pcl/dtbgSgo51yPc+5uSeUKPsTPq19IYieyXdKq8PlSSXsynEPxS/dzp3NF5AMzi245WKrgUzAkjAs26/y1gg9oXpb0w3QjKChOGS7CuWZIph9LapH0m3Chl1skPSrpNUlvSvqtc26nzwJRGGb2uJl1hIcNknqUZ79QNm7VTR5PSXrRzFZL+pyktxQMMY4+h+KXri1EneuA6FyT7nFJm8zsLUmnnHMHP+sLMHk559ZkOnbOPSPpmQKXhHhIvQiXpJ8p/d8OFKmoL3DOPSLpkTRvubqgBSEOfiXpD2bmJL3qnNtpZnn1CxZ8+JcsZjZbQYp9JfrEK905FD9+7rgcM7tK0jJJL6SZYwYgofjbAWC0fPqFRAYyAAAAAIiDJM4hAwAAAIBYIJABAAAAgCcEMgAAAADwhEAGAAAAAJ4QyAAAAADAk/8D8YXsEBpfwWgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "plt.plot(data.iloc[100:130][data.columns[3]], label=data.columns[3])\n",
    "plt.plot(data.iloc[100:130][data.columns[5]], label=data.columns[5])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Lly8nISGBpKQk7HY7XV1dWK1WkpKSsFgsrF69etA8+u7te86bb77JM888w7x58wgPD8dqtfL+++/7vPeLL74gOjrae+/58+cBaGpqYsGCBd64rq4uMjMzSU5O5uWXX/a2NzQ08PDDD/v9Tn3vkZyczLJly2hpaWH69One608++SSvvfaa3z5ERERERGRwVz1Vcrj83Qd/x783//t17fNvIv6G9XPWD3p9x44dJCUlsW7dOgoLC6mrqyMxMbFfTEZGBhkZGVy8eBGz2UxOTg6lpaXExsZSUVFBTk4Oe/bsAaC0tBSz2cyKFSuorKwEYO/evURHR5OWlub3/LK+e/ssWbKEwsJCCgsLvX35Ultby9NPP80TTzzhbXM6nRQUFNDW1tav/1mzZlFSUkJ6ejp2u51z586xdu1a3G63n69Iv/coLCzk2LFjTJ06lfr6eu677z6OHDnC2rVrr9iHiIiIiIj4pp0e/YiKiqKiogKHw0F5efmAou1ymzdvJi8vj8jISGpra7FYLACYzWaOHz/ujfN4PLjdbgIDA71tPT09tLS0EBwcPKDfa3Xs2DHKy8uZOXMmTz31FAABAQHs3r0bo9HojauqqvKe4WaxWKirqyM0NJR9+/YN+VkejweXy0VwcDCpqalUVlZy7tw5DAYDkydPvr4vJiIiIiJyG7lpRtz8jYzdKJmZmbS3t5OdnU1KSgrt7e04HA7vdZvNxsaNG2lqamL//v0cPXoUgNbWVsaNGwfA2LFjuXDhAgDFxcU0NzeTmZmJzWZj06ZN2O12GhsbSUxMJCYmZtBciouLMZlM3mcO1eLFi3n22WcZO3YsixYt4uTJkzzwwAMD4tra2oiKigIgIiKCpqYmUlJShvwcu91OQEAAKSkpWCwWQkJCKCkpYcKECTz00END7kdERERERAa6aQq34eBwOEhLS+ORRx4hLy+PtLQ0tm3bNiBuw4YNlJSUMGpU7+c0Go3e6YVtbW0YjUacTielpaXU1NQQFBTkPdB87969TJw4kaVLl7Jz507y8/N95vLNqZJDNX/+fIKCggBISEjA4XD4LNxCQkJob2/HZDLhdrsJCQm5quf0TZXsk5CQQENDA++88w7Lli276rxFRERERORrmirpR3l5ORUVFQQEBBAfH09HR8eAmBMnTnD+/HkWL17sbZs7dy5VVVUAVFdXM2fOHO+1lStXsn37dnp6vt5kc/To0RiNRlpbW6/7O6SmptLY2MhXX33Fu+++S3x8vM+4WbNmUVNTA8BHH33EtGnTrum5BoOBefPm8dZbb32rglNERERERL6mETc/1qxZQ25uLq+88gomk4k33nhjQMzWrVs5deoUVqsV6N00ZNWqVeTn5zN//nxiY2Ox2+0cOnQIgPDwcGw2m3ftmN1ux+PxYDKZyM3N5ciRI9TX17Nq1arr8g7PPfccKSkpBAYG8vjjjxMXF+czrqCggPT0dKqrq6mvr2fu3Lk+43bt2kVgYCBLliy54rNTU1NxuVz91vOJiIiIiMjVM/ja4n44zJ4921NXV9evzd8ui3L9nTlzhpqaGlJTUzGZTMOWh37uIiIiInI7MhgMJzwez2xf1zTidos4e/YsOTk5/dri4uIoKysbch9Tpkzx7iwpIiIiIiIjhwq3W8SkSZO86+pEREREROTWos1JRERERGRYXOy5SMn/U0Kju3G4UxEZ8VS4iYiIiMiwOOU6xT7HPg7/+fBwpyIy4qlwExEREZFh4ex0AvCJ65NhzkRk5FPhJiIiIiLDwtXhAlS4iQyFCjc/2trayMrKYuHCheTn5+Pr6ISDBw9itVqxWq3ExMSwZcsW3G43WVlZmM1mCgoK6O7uZvny5SQkJJCUlITdbqerqwur1UpSUhIWi4XVq1cPmkffvX3PefPNN3nmmWeYN28e4eHhWK1W3n//fZ/3fvjhhyxatIjk5GT+6Z/+CYCuri4yMzNJTk7m5ZdfHrQNerfmf/jhh/1+p773SE5OZtmyZbS0tDB9+nTv9SeffJLXXnvNbx8iIiJy+7l8xO2S59IwZyMyst00u0qe/T//h86Gf7+ufQbd+zdMeuqpQa/v2LGDpKQk1q1bR2FhIXV1dSQmJvaLycjIICMjg4sXL2I2m8nJyaG0tJTY2FgqKirIyclhz549AJSWlmI2m1mxYgWVlZUA7N27l+joaNLS0vyeX9Z3b58lS5ZQWFhIYWGhty9fiouL+ed//meio6NJTk4mOzubiooKZs2aRUlJCenp6djtdrZt2zag7dy5c6xduxa3233Fb9n3HoWFhRw7doypU6dSX1/Pfffdx5EjR1i7du0V+xAREZHbS0tnCwDt3e2ccZ8hOjR6mDMSGbk04uZHVFQUFRUVOBwOysvLBxRtl9u8eTN5eXlERkZSW1uLxWIBwGw2c/z4cW+cx+PB7XYTGBjobevp6aGlpYXg4ODr/g7Nzc3cddddGAwGIiMjuXDhAlVVVd7z2iwWC3V1dT7bQkND2bdv35Cf5fF4cLlcBAcHk5qaSmVlJefOncNgMDB58uTr/m4iIiJyc3N2OL2/1nRJEf9umhE3fyNjN0pmZibt7e1kZ2eTkpJCe3s7DofDe91ms7Fx40aamprYv38/R48eBaC1tZVx48YBMHbsWC5cuAD0jn41NzeTmZmJzWZj06ZN2O12GhsbSUxMJCYmZtBciouLMZlM3mcOVXJyMi+99BIRERF89tlnPPDAA7S1tREVFQVAREQETU1NPttSUlKG/By73U5AQAApKSlYLBZCQkIoKSlhwoQJPPTQQ0PuR0RERG4frk4XkWMi+bLjSz5xfYL1LutwpyQyYt00hdtwcDgcpKWl8cgjj5CXl0daWhrbtm0bELdhwwZKSkoYNar3cxqNRu/0wra2NoxGI06nk9LSUmpqaggKCsJgMAC9UwwnTpzI0qVL2blzJ/n5+T5z+eZUyaEqKyvj3/7t39i4cSPr16/HYDAQEhJCe3s7JpMJt9tNSEiIz7ar0TdVsk9CQgINDQ288847LFu27KrzFhERkVufs9NJdGg0gQGBGnETuQJNlfSjvLyciooKAgICiI+Pp6OjY0DMiRMnOH/+PIsXL/a2zZ07l6qqKgCqq6uZM2eO99rKlSvZvn07PT093rbRo0djNBppbW297u8QEBBAXFwcALm5uQDMmjWLmpoaAD766COmTZvms+1aGAwG5s2bx1tvvfWtCk4RERG59bV0thAeFM49YffwiVOFm4g/GnHzY82aNeTm5vLKK69gMpl44403BsRs3bqVU6dOYbVagd5NQ1atWkV+fj7z588nNjYWu93OoUOHAAgPD8dms3nXjtntdjweDyaTidzcXI4cOUJ9fT2rVq26bu/xzDPP8Hd/93feUb6CggLS09Oprq6mvr6euXPnEhUVNaDNl127dhEYGMiSJUuu+NzU1FRcLle/9XwiIiIifZwdTuLC44gYE0FtYy3dl7oZdYf+eirii8HXFvfDYfbs2Z66urp+bf52WZRrc+bMGWpqakhNTcVkMg3aNhz0cxcREbn1eTweEl9P5NG/eZTY8Fiernmat/7HW9xtunu4UxMZNgaD4YTH45nt65r+SeMWcfbsWXJycvq1xcXFUVZW5jN+ypQp3l0k/bWJiIiI3Ajt3e109nQSFhTGjLAZAHzi/ESFm8ggVLjdIiZNmuRdVyciIiIy0vWd4RY+Jpy7TXdjwMAnrk94CO1GLeKLNicRERERke+cs7P3DLewoDDGjBrDVONU7Swp4ocKNxERERH5zrk6XEBv4QYwI2wGDqfD3y0itzUVbiIiIiLynfOOuI35unD7r9b/orOnczjTEhmxVLiJiIiIyHfO1dk74hYeFA7AjPAZ9Hh6+Kzls2HMSmTkUuHmR1tbG1lZWSxcuJD8/Hx8HZ1w8OBBrFYrVquVmJgYtmzZgtvtJisrC7PZTEFBAd3d3SxfvpyEhASSkpKw2+10dXVhtVpJSkrCYrGwevXqQfNYvny593DsPj09PRQVFbFgwQIKCgq4dOmSz3u/+OILoqOjvTmeP38egB//+MckJSXxwgsveGN9tTU1NbFgwQK/36nv3RYsWEBmZiatra3ExMTQ1tYGwK9//Wuef/55v32IiIjI7cXV6cKAAWOgEYAZpt6dJR0uTZcU8eWm2VWyes9/8pf/cl/XPu+8K4QFP/zeoNd37NhBUlIS69ato7CwkLq6OhITE/vFZGRkkJGRwcWLFzGbzeTk5FBaWkpsbCwVFRXk5OSwZ88eAEpLSzGbzaxYsYLKykoA9u7dS3R0NGlpaVd1ftnu3bvp7Oykurqa9evXc+DAAbKzswfE1dbW8vTTT/PEE0942/bv309PTw/vv/8+jz32GA6Hg48//nhA25133klBQYG3APOn791eeOEFdu3ahdVq5b333iM9PZ3f/e53bNiwYUjvJSIiIrcHZ4cTY5CRgDsCAIgxxjDqjlF84tQGJSK+aMTNj6ioKCoqKnA4HJSXlw8o2i63efNm8vLyiIyMpLa2FovFAoDZbOb48ePeOI/Hg9vtJjAw0NvW09NDS0sLwcHBQ87t0KFDZGRkALB06VLGjx/vM+7YsWOUl5czc+ZMnnrqKQCqqqq857U99NBD1NTU+GwLCAhg9+7dGI3GIefldDoJDg4mNTWVyspKenp6OHnypN9vJyIiIrcfV6fLO00SYHTAaKYZp2lnSZFB3DQjbv5Gxm6UzMxM2tvbyc7OJiUlhfb2dhyOr4fvbTYbGzdupKmpif3793P06FEAWltbGTduHABjx47lwoULABQXF9Pc3ExmZiY2m41NmzZht9tpbGwkMTGRmJiYIefW1NREREQEADNnzhw0bvHixTz77LOMHTuWRYsWcfLkSdra2oiKigIgIiKCDz/80Gfb1RRsxcXFhISEEB8fz6OPPkpLSwt///d/z/Hjx5kzZw4BAQFD7ktERERufa5Ol3dHyT6xYbGc/MvJYcpIZGS7aQq34eBwOEhLS+ORRx4hLy+PtLQ0tm3bNiBuw4YNlJSUMGpU7+c0Go243b3TOtva2jAajTidTkpLS6mpqSEoKAiDwQD0TpWcOHEiS5cuZefOneTn5w8pt8ufceDAAdxuN3l5eQPi5s+fT1BQEAAJCQk4HA5CQkJob28HwO12c+nSJZ9tV6NvqmSfO++8k8DAQF5//XVSU1Ovqi8RERG59bk6XEwOmdyvbUb4DN7+7G3autoYN3rcMGUmMjJpqqQf5eXlVFRUEBAQQHx8PB0dHQNiTpw4wfnz51m8eLG3be7cuVRVVQFQXV3NnDlzvNdWrlzJ9u3b6enp8baNHj0ao9FIa2vrkHNLTk7m8OHDABw+fJiwsDCfcampqTQ2NvLVV1/x7rvvEh8fz6xZs7ybnXz00UdMmzbNZ9u1Sk1NpaysTIWbiIiIDODsdA4YcZsR1rtBySnXqeFISWRE04ibH2vWrCE3N5dXXnkFk8nEG2+8MSBm69atnDp1CqvVCsCSJUtYtWoV+fn5zJ8/n9jYWOx2O4cOHQIgPDwcm83Gvn37ALDb7Xg8HkwmE7m5uRw5coT6+npWrVrV7zmFhYWEhIQA8NRTT1FUVMRjjz2G2Wxm+vTppKen+3yH5557jpSUFAIDA3n88ceJi4tj8uTJLFiwgDNnzvD2229z7NgxDAbDgDZfBsvPl9TUVA4cOOCdgikiIiICvWv+XR3917hB71RJ6C3cHhj/wHCkJjJiGXxtcT8cZs+e7amrq+vXdjW7LMrVcTqdHD58GIvFwqRJkwZtGw76uYuIiNzavur6irm75vI/Z/1PHot/zNt+yXOJua/PxR5nZ13iumHMUGR4GAyGEx6PZ7avaxpxu0WcPXuWnJycfm1xcXGUlZX5jA8PD/fuIumvTUREROR6++bh233uMNzB3WF360gAER9UuN0iJk2a5F1XJyIiIjKSOTudAJiCTAOuzQibwftn3v+uUxIZ8bQ5iYiIiIh8p1wdfx1xGxM+4FpsWCzn2897Y0Sklwo3EREREflO9Y24fXNXSeg9EgDQQdwi36DCTURERES+Uy2dLcDANW7w9ZEAKtxE+lPhJiIiIiLfKWeHEwMGQgNDB1ybOHYioaNDVbiJfIMKNz/a2trIyhUx3R0AACAASURBVMpi4cKF5Ofn4+vohIMHD2K1WrFarcTExLBlyxbcbjdZWVmYzWYKCgro7u5m+fLlJCQkkJSUhN1up6urC6vVSlJSEhaLhdWrVw+ax/Lly72HY/fp6emhqKiIBQsWUFBQwKVLl3ze+8UXXxAdHe3N8fz58wA0NTWxYMECb1xXVxeZmZkkJyfz8ssve9sbGhp4+OGH/X6nvvdITk5m2bJltLS0MH36dO/1J598ktdee81vHyIiInL7cHW6MAWZCLgjYMA1g8HAjPAZOJyOYchMZOS6aXaV/LdX/y/n/vzpde1zQszdpCwvGvT6jh07SEpKYt26dRQWFlJXV0diYmK/mIyMDDIyMrh48SJms5mcnBxKS0uJjY2loqKCnJwc9uzZA0BpaSlms5kVK1ZQWVkJwN69e4mOjiYtLe2qzi/bvXs3nZ2dVFdXs379eg4cOEB2dvaAuNraWp5++mmeeOIJb5vT6aSgoIC2tjZvW2lpKbNmzaKkpIT09HTsdjvnzp1j7dq1uN3uK+bT9x6FhYUcO3aMqVOnUl9fz3333ceRI0dYu3btkN5LREREbn3ODqfP9W19ZoTN4N0/v4vH48FgMHyHmYmMXBpx8yMqKoqKigocDgfl5eUDirbLbd68mby8PCIjI6mtrcVisQBgNps5fvy4N87j8eB2uwkMDPS29fT00NLSQnBw8JBzO3ToEBkZGQAsXbqU8ePH+4w7duwY5eXlzJw5k6eeegqAgIAAdu/ejdFo9MZVVVV5z3CzWCzU1dURGhrKvn37hpyTx+PB5XIRHBxMamoqlZWVnDt3DoPBwOTJk4fcj4iIiNzaWjpbfO4o2eeesHto6WzhL+1/+Q6zEhnZbpoRN38jYzdKZmYm7e3tZGdnk5KSQnt7Ow7H18P2NpuNjRs30tTUxP79+zl69CgAra2tjBs3DoCxY8dy4cIFAIqLi2lubiYzMxObzcamTZuw2+00NjaSmJhITEzMkHNramoiIiICgJkzZw4at3jxYp599lnGjh3LokWLOHnyJA888MCAuLa2NqKiogCIiIigqamJlJSUIedjt9sJCAggJSUFi8VCSEgIJSUlTJgwgYceemjI/YiIiMitz9npZErIlEGvx4bFAuBwORg/1vc/TovcbjTi5ofD4SAtLY0//vGPnD9/HrPZTFVVlfe/jRs3ArBhwwZKSkoYNaq3DjYajd7phW1tbd6RrdLSUp544gnuuece77D/3r17cTgc9PT0sHPnziHndvkzDhw4MOi98+fPJzQ0lICAABISEvoVnpcLCQmhvb0dALfbPeiaucHs3buXmpoaNm3aBEBCQgINDQ288847pKamXlVfIiIicmtzdbh87ijZx3skgFMblIj0UeHmR3l5ORUVFQQEBBAfH09HR8eAmBMnTnD+/HkWL17sbZs7dy5VVVUAVFdXM2fOHO+1lStXsn37dnp6erxto0ePxmg00traOuTckpOTOXz4MACHDx8mLMz3PPHU1FQaGxv56quvePfdd4mPj/cZN2vWLO8GKB999BHTpk0bci6+GAwG5s2bx1tvvYXZbL6mvkREROTW4fF4cHY6CRsz+Bq3iDERRIyJ0M6SIpe5aaZKDoc1a9aQm5vLK6+8gslk4o033hgQs3XrVk6dOoXVagVgyZIlrFq1ivz8fObPn09sbCx2u51Dhw4BEB4ejs1m864ds9vteDweTCYTubm5HDlyhPr6elatWtXvOYWFhYSEhADw1FNPUVRUxGOPPYbZbGb69Omkp6f7fIfnnnuOlJQUAgMDefzxx4mLi/MZV1BQQHp6OtXV1dTX1zN37lyfcbt27SIwMJAlS5Zc8fulpqbicrn6recTERGR21t7dztdl7r8jrhB73RJFW4iXzP42uJ+OMyePdtTV1fXr+1qdlmUa3fmzBlqampITU3FZDINWx76uYuIiNy6vnB/Qdq+NH4x/xdkxWYNGvfiBy+y37GfYz86xh0GTRKT24PBYDjh8Xhm+7qmEbdbxNmzZ8nJyenXFhcXR1lZ2ZD7mDJlindnSREREZEbwdXhAvB7HAD0HgnQ3t3OGfcZokOjv4vUREY0FW63iEmTJnnX1YmIiIiMVM5OJ4Df4wCgt3ADOOU6pcJNBG1OIiIiIiLfIVfn0Ebc7gm7B+g9EkBEVLiJiIiIyHeob6rklUbcQgNDmTRukjYoEfkrFW4iIiIi8p1xdjq5w3AHoYGhV4ydETZDZ7mJ/JUKNz/a2trIyspi4cKF5Ofn42sHzoMHD2K1WrFarcTExLBlyxbcbjdZWVmYzWYKCgro7u5m+fLlJCQkkJSUhN1up6urC6vVSlJSEhaLhdWrVw+aR9+9CxYsIDMzE7fbTU9PD0VFRSxYsICCgoJBD8w+ffo0VqsVm81GUVGR9x0aGhp4+OGHvXEulwuLxUJycjJvv/02ADU1NcyYMQOr1coPfvCDIefX2tpKTEwMbW1tAPz617/m+eefv/IHFxERkVueq8OFKdA0pJ0iY8Ni+bTlU7ovdX8HmYmMbDfN5iSufz3FxTNt17XPwCnjCMu8Z9DrO3bsICkpiXXr1lFYWEhdXR2JiYn9YjIyMsjIyODixYuYzWZycnIoLS0lNjaWiooKcnJy2LNnDwClpaWYzWZWrFhBZWUlAHv37iU6Opq0tDS/2+D33fvCCy/w+uuvExoaSmdnJ9XV1axfv54DBw6QnZ094L6ysjJ+85vfcO+997J48WI+/vhjxo0bx9q1a3G73d64jRs38thjj5Gfn8+iRYtIS0vjgw8+oLS0tN/h4oO5PL9du3ZhtVp57733SE9P53e/+x0bNmy4Yh8iIiJy63N1uvwevn25GeEz6LrUxenW09xtuvsGZyYysmnEzY+oqCgqKipwOByUl5cPKNout3nzZvLy8oiMjKS2thaLxQKA2Wzm+PHj3jiPx4Pb7e53KHVPTw8tLS0EBwdfMSen00lwcDCHDh0iIyMDgKVLlzJ+/Hif8b/85S+9xeCXX37JnXfeSWhoqPcA8D6///3vWbJkCQEBAcTFxfHZZ59x7NgxNm3aREJCAi+99NIVc7s8v9TUVCorK+np6eHkyZN+v52IiIjcPlydrisevt2nb2dJTZcUuYlG3PyNjN0omZmZtLe3k52dTUpKCu3t7TgcX+9sZLPZ2LhxI01NTezfv5+jR48C0Nrayrhx4wAYO3YsFy5cAKC4uJjm5mYyMzOx2Wxs2rQJu91OY2MjiYmJxMTEDJpLcXExISEhxMfH8+ijj7Jr1y4iIiIAmDlz5hXfZffu3dx///1MmTLF5/VRo0YREhICQEREBE1NTaxYsYK//du/pbu7m1mzZvHoo48SGRk5pPxaWlr4+7//e44fP86cOXMICAi4Yo4iIiJy63N2OokOGdr2/neb7saAgU9cn/AQD93gzERGtpumcBsODoeDtLQ0HnnkEfLy8khLS2Pbtm0D4jZs2EBJSQmjRvV+TqPR6J2G2NbWhtFoxOl0UlpaSk1NDUFBQRgMBqB3quTEiRNZunQpO3fuJD8/32cufVMR+1z+jAMHDuB2u8nLy/N576effso//uM/eqdn+nJ5YeV2u7l06RI2m41Ro0YxatQo7yjcYIXbN/O78847CQwM5PXXXyc1NXXQ54qIiMjtxdXh4r/d+d+GFDtm1BimGqdqZ0kRNFXSr/LycioqKggICCA+Pp6Ojo4BMSdOnOD8+fP91oHNnTvXexh2dXU1c+bM8V5buXIl27dvp6enx9s2evRojEYjra2tQ84tOTmZw4cPA3D48GHCwnzPFXc6nTz66KO8/PLLmEymQfu7//77qaurA+Cjjz4iJiYGs9mM2+2mqamJP/zhD8yYMWPI+QGkpqZSVlamwk1ERESA3iUjzk7nFc9wu9w9pntUuImgws2vNWvW8Oqrr2K1Wvnggw98joZt3bqVU6dOeXeWfOmll1i1ahWffvop8+fPJzg4GLvd7o0PDw/HZrN515jZ7XbmzZtHY2Mjubm5HDlyZEjryYqKimhubsZsNnPhwgXS09N9xr344oucPn2a4uJi74YhvjzxxBP8+Mc/pqioiNDQUKKiovhf/+t/kZCQQFpaGv/wD/+AyWQacn7QW7jFxcURFRU1pHgRERG5tX3V/RXdl7qHvMYNejcoOX3hNJ09nTcwM5GRz+Bri/vhMHv2bE/fiE8ff7ssyvX3ySef8Mc//pHMzEyCgoKGLQ/93EVERG5Nn7d+zuL9i/nF/F+QFZs1pHve+dM7rP39Wt7MfJO4iLgbnKHI8DIYDCc8Hs9sX9e0xu0WcfbsWXJycvq1xcXFUVZWNuQ+ZsyYcdXTIUVERESGytXpAiB8zFWMuP11Z0mHy6HCTW5rKtxuEZMmTfKuqxMREREZiZwdToCrWuMWY4xh1B2jdCSA3Pa0xk1EREREvhPfZsRtdMBophmnaYMSue2pcBMRERGR70Rf4XY1I24AsWGxKtzktqfCTURERES+E84OJ3cY7iA0MPSq7psRPoMv3F/wVddXNygzkZFPhZuIiIiIfCdcnS7CgsK4w3B1fwW9J+weAE65Tt2ItERuCirc/GhrayMrK4uFCxeSn5+Pr6MTDh486D3DLSYmhi1btuB2u8nKysJsNlNQUEB3dzfLly8nISGBpKQk7HY7XV1dWK1WkpKSsFgsrF69etA8+u5dsGABmZmZuN1uenp6KCoqYsGCBRQUFHDp0iWf937xxRdER0d7czx//jwATU1NLFiwwBvX1dVFZmYmycnJvPzyy972hoYGHn74Yb/fqe89kpOTWbZsGS0tLUyfPt17/cknn+S1117z24eIiIjc+voKt6sVGxYLoOmSclu7aXaVfPvttzl79ux17XPSpEksXrx40Os7duwgKSmJdevWUVhYSF1dHYmJif1iMjIyyMjI4OLFi5jNZnJycigtLSU2NpaKigpycnLYs2cPAKWlpZjNZlasWEFlZSUAe/fuJTo6mrS0NL/nl/Xd+8ILL/D6668TGhpKZ2cn1dXVrF+/ngMHDpCdnT3gvtraWp5++mmeeOIJb5vT6aSgoIC2trZ+/c+aNYuSkhLS09Ox2+2cO3eOtWvX4na7r/gt+96jsLCQY8eOMXXqVOrr67nvvvs4cuQIa9euvWIfIiIicmv7toVbVEgUYwLG4HA5bkBWIjcHjbj5ERUVRUVFBQ6Hg/Ly8gFF2+U2b95MXl4ekZGR1NbWYrFYADCbzRw/ftwb5/F4cLvdBAYGett6enpoaWkhODj4ijk5nU6Cg4M5dOgQGRkZACxdupTx48f7jD927Bjl5eXMnDmTp556CoCAgAB2796N0Wj0xlVVVfHDH/4QAIvFQl1dHaGhoezbt++KOV3+bi6Xi+DgYFJTU6msrOTcuXMYDAYmT5485H5ERETk1uTscH6rwi3gjgDuDrtbRwLIbe2mGXHzNzJ2o2RmZtLe3k52djYpKSm0t7fjcHz9Lz02m42NGzfS1NTE/v37OXr0KACtra2MGzcOgLFjx3LhwgUAiouLaW5uJjMzE5vNxqZNm7Db7TQ2NpKYmEhMTMyguRQXFxMSEkJ8fDyPPvoou3btIiIiAoCZM2cOet/ixYt59tlnGTt2LIsWLeLkyZM88MADA+La2tqIiooCICIigqamJlJSUob8rex2OwEBAaSkpGCxWAgJCaGkpIQJEybw0EMPDbkfERERuXW5Ol18f/z3v9W9M8Jm8P6Z969zRiI3j5umcBsODoeDtLQ0HnnkEfLy8khLS2Pbtm0D4jZs2EBJSQmjRvV+TqPR6J1e2NbWhtFoxOl0UlpaSk1NDUFBQRgMBqB3iuHEiRNZunQpO3fuJD8/32cufVMl+1z+jAMHDuB2u8nLyxtw3/z58wkKCgIgISEBh8Phs3ALCQmhvb0dk8mE2+0mJCTkaj6Vd6pkn4SEBBoaGnjnnXdYtmzZVfUlIiIitx6Px/Otp0pC7zq3fzn1L7g6XISN+XZ9iNzMNFXSj/LycioqKggICCA+Pp6Ojo4BMSdOnOD8+fP9RgTnzp1LVVUVANXV1cyZM8d7beXKlWzfvp2enh5v2+jRozEajbS2tg45t+TkZA4fPgzA4cOHCQvz/QdYamoqjY2NfPXVV7z77rvEx8f7jJs1axY1NTUAfPTRR0ybNm3IufhiMBiYN28eb731Vr+CU0RERG5PbV1tdF/qvqrDty83I3wGoA1K5PalETc/1qxZQ25uLq+88gomk4k33nhjQMzWrVs5deoUVqsVgCVLlrBq1Sry8/OZP38+sbGx2O12Dh06BEB4eDg2m827dsxut+PxeDCZTOTm5nLkyBHq6+tZtWqV39yKiop47LHHMJvNTJ8+nfT0dJ9xzz33HCkpKQQGBvL4448TFxfnM66goID09HSqq6upr69n7ty5PuN27dpFYGAgS5Ys8Zsf9BaNLper33o+ERERuT05O50AmIJM3+r+GWFfF26zJ82+bnmJ3CwMvra4Hw6zZ8/21NXV9Wvzt8uiXH9nzpyhpqaG1NRUTKZv94fq9aCfu4iIyK3n4/Mf86Pf/oiXbC+x8K6FV32/x+Nh/hvzybg7g2fmPXMDMhQZfgaD4YTH4/H5LxMacbtFnD17lpycnH5tcXFxlJWVDbmPKVOmeHeWFBEREbmeXJ0ugG+9Ps1gMDAjbIamSsptS4XbLWLSpEnedXUiIiIiI01f4RYe9O3WuEHvOrfDfz6Mx+PxbvQmcrvQ5iQiIiIicsM5O65tjRv0rnNr6WzhL+1/uV5pidw0VLiJiIiIyA3n6nQRYAggNDD0W/cRGxYLgMPluEKkyK1HhZuIiIiI3HCuThemIBN3GL79Xz+9RwI4tc5Nbj8q3ERERETkhnN1uq5pfRtAxJgIIsZEaIMSuS2pcPOjra2NrKwsFi5cSH5+Pr6OTjh48CBWqxWr1UpMTAxbtmzB7XaTlZWF2WymoKCA7u5uli9fTkJCAklJSdjtdrq6urBarSQlJWGxWFi9evWgefTdu2DBAjIzM3G73VitVubNm0diYiL/8i//AkBhYSEPPvggkydPxmq18qc//clnf3/4wx9ITk7GYrHw/PPPe9vfe+89fvKTn3h//6c//YnExEQsFgsffvhhvz7KysooKSkZNOfp06d7c1y3bh0NDQ0kJyd7r2dnZ/Pee+8Ner+IiIjcWpwdzmta39YnNixWhZvclm6aXSX/8z830epuuK59hobcy/e+9+yg13fs2EFSUhLr1q2jsLCQuro6EhMT+8VkZGSQkZHBxYsXMZvN5OTkUFpaSmxsLBUVFeTk5LBnzx4ASktLMZvNrFixgsrKSgD27t1LdHQ0aWlpfs8v67v3hRde4PXXXwfgzTffpKuri5kzZ+JwOCgvL6eqqoqdO3dSXl4+6Htt3bqViooKJkyYwP3338/Pf/5zGhoaeP7555k6dao3bs2aNfzDP/wDs2fPxm638/bbbwNw7tw5fvGLX/Qr8r4pICDAu8vlokWL+PGPf0xTUxMXLlwgJCSEEydOMH/+/EHvFxERkVuLq9NFjDHmmvu5J+weDnxygEueS9c07VLkZqP/2/2IioqioqLCWxR9s2i73ObNm8nLyyMyMpLa2losFgsAZrOZ48ePe+M8Hg9ut5vAwEBvW09PDy0tLQQHB18xJ6fT2S9u+vTpzJkzh2PHjg35vcrKypgwYQJdXV10d3czduxY7rrrrgHFXn19PVarlZCQEO644w66uroAWLduHT/96U+H9Kzu7m7a2toYM2YMNpuNqqoqTpw4wYMPPsjo0aOHnLOIiIjc3JwdTsKCvt0ZbpebET6Dr7q/orGt8TpkJXLzuGlG3PyNjN0omZmZtLe3k52dTUpKCu3t7TgcX+9iZLPZ2LhxI01NTezfv5+jR48C0Nrayrhx4wAYO3YsFy5cAKC4uJjm5mYyMzOx2Wxs2rQJu91OY2MjiYmJxMQM/q9QxcXFhISEEB8fz6OPPsrLL7/svRYZGYnL5brq9/vVr37Fj370I0aPHk1UVBSfffZZv+thYV//4Woymfjyyy/593//d8aOHUtycrLfc+N6enqwWq10d3eTn59PTEwMaWlpVFZWMmXKFNLS0q46XxEREbk5eTweWjpbCB9zbWvc4OudJT9xfkJUSNQ19ydys7hpCrfh4HA4SEtL45FHHiEvL4+0tDS2bds2IG7Dhg2UlJQwalTv5zQajbjdbqB3nZzRaMTpdFJaWkpNTQ1BQUHeQyP37t3LxIkTWbp0KTt37iQ/P99nLn1TJX1pbm4mIiLiqt6ttraW3/72t94pm77cccfXA7Jut5uLFy+yadMm9u/fzx/+8Ae//V8+VbLPD37wA0pKSpg4cSJlZWVXla+IiIjcvNxdbro93ddlxO2esHuA3iMBFt618Jr7E7lZaKqkH+Xl5VRUVBAQEEB8fDwdHR0DYk6cOMH58+dZvHixt23u3LneoqW6upo5c+Z4r61cuZLt27fT09PjbRs9ejRGo5HW1tarzvH06dN8+OGHJCUlDfmezz77jJ/+9Kfs2rXL73TFsLAwzp49i8fj4dSpUzQ2NnLu3Dkefvhhfv7zn/Pqq6/y5ptvDvm5JpMJk8nEF198wd133z3k+0REROTm5uronRl0PQq30MBQJo2bpA1K5LajETc/1qxZQ25uLq+88gomk4k33nhjQMzWrVs5deoUVqsVgCVLlrBq1Sry8/OZP38+sbGx2O12Dh06BEB4eDg2m419+/YBYLfb8Xg8mEwmcnNzOXLkCPX19axateqK+S1ZsoSAgADeeOMNwsOHPvVg/fr1NDc3k5ubC/SueYuLixsQ97Of/YysrCxiYmJISUlh7ty5fPzxxwBUVVVRVVXFkiVL+NWvfsWcOXMGHRG8XGpqKk1NTUPOVURERG5+zk4nwHWZKgkwI2yGznKT247B1xb3w2H27Nmeurq6fm3+dlmU78ZHH33En//8Z/77f//v/aZO3kj6uYuIiNxafv/57/nZ737G6+mv88D4B665v1/V/YqdDTv5IPcDRt2hcQi5dRgMhhMej2e2r2v6P/0W9sc//pGf//zn/doWLlzY7+y2K/n+97/P97///eudmoiIiNxGXJ29UyWv9QDuPjPCZ9B1qYvTrae526TlF3J7UOF2C3vwwQf97vwoIiIi8l1wdvROlTSNufYDuOHrDUpOuU6pcJPbhjYnEREREZEbytXpIsAQQOjo0OvS392muzFg0Do3ua2ocBMRERGRG8rV6SIsKMx7HNK1Ch4VzF2hd+FwOa4cLHKLUOEmIiIiIjeUq8N13XaU7DMjbIaOBJDbigo3EREREbmhnJ1OTEHXZ31bnxnhMzh94TSdPZ3XtV+RkUqFmx9tbW1kZWWxcOFC8vPz8XV0wsGDB7FarVitVmJiYtiyZQtut5usrCzMZjMFBQV0d3ezfPlyEhISSEpKwm6309XVhdVqJSkpCYvFwurVqwfNo+/eBQsWkJmZidvt5plnnmHevHmEh4djtVp5//33fd57+vRprFYrNpuNoqIi7zs0NDTw8MMPe+NcLhcWi4Xk5GTefvttb/t7773HT37yE7/fafr06VitVubNm8e6detoaGggOTnZez07O5v33nvPbx8iIiJy63J1uK7bjpJ9YsNi6fH08FnLZ9e1X5GR6qbZVfJZx+f8v+7269pnfEgwm2KjB72+Y8cOkpKSWLduHYWFhdTV1ZGYmNgvJiMjg4yMDC5evIjZbCYnJ4fS0lJiY2OpqKggJyeHPXv2AFBaWorZbGbFihVUVlYCsHfvXqKjo0lLS/N7flnfvS+88AKvv/46L7zwAoWFhRQWFnr78qWsrIzf/OY33HvvvSxevJiPP/6YcePGsXbtWtxutzdu48aNPPbYY+Tn57No0SLS0tKora3l+eefZ+rUqX6/Y0BAgHf3ykWLFvHjH/+YpqYmLly4QEhICCdOnGD+/Pl++xAREZFbl6vTRdiYsOva54ywGQA4XA7iIuKua98iI5FG3PyIioqioqICh8NBeXn5gKLtcps3byYvL4/IyEhqa2uxWCwAmM1mjh8/7o3zeDy43W4CAwO9bT09PbS0tBAcHHzFnJxO55Di+vzyl7/0FoNffvkld955J6Ghoezbt69f3O9///v/n737D4u6TBc//h6H3yIjkmKiIS6sW7IlKciPEYYxY5Blu1AnMZjUpKyOqNd2suOu62Lanrb2m9/T6HfliFmrWUlKe/aoa6KLiusvSK2zejb8wVaGxOYMMATIDPP9g5jNGBAVHAbv13Wd69jzeebzuT+DV9vN/Tz3w8yZM1EqlYwdO5bKykpGjRpFQUFBt59ltVppaGjAx8cHrVZLSUkJ5eXljB8/Hk9Pz27fRwghhBD9h91ux9zc8xW30IBQPAZ4SGdJccdwm4pbV5Wx3pKenk5jYyPTp08nOTmZxsZGKir+2b1Iq9WyYsUKqqur2bFjB4cPHwagvr6egQMHAuDn50ddXR0Aubm5XLlyhfT0dLRaLatWrUKv11NVVUV0dDShoaGdxpKbm4u/vz+RkZHMnj37ht/lvffeY9y4cYwYMcLpdQ8PD/z9/QEYMmQI1dXVxMbGUllZed1722w2NBoNVqsVg8FAaGgoOp2O4uJiRowYgU6nu+F4hRBCCNE/1LfUY7PbenyPm6fSk9EBozlvPt+j9xWir3KbxM0VKioq0Ol0zJgxg+zsbHQ6HRs2bOgwb9myZeTl5eHh0fZ1BgQEOJYhNjQ0EBAQgMlkwmg0Ulpaire3t6MdbmFhIcHBwcyaNYstW7ZgMBicxtK+VPJmXLhwgd/+9rddLqlUKpWOP1ssFlpbW7t9/+8ulWw3ZcoU8vLyCA4OJj8//4ZjFkIIIUT/YG4yA/R4V0loWy75yT8+6fH7CtEXyVLJLhQUFFBUVIRSqSQyMpKmpqYOc8rLy6mpqSE1NdUxNmnSJEcic+jQIWJiI+JFAAAAIABJREFUYhzXFixYwMaNG7HZbI4xT09PAgICqK+v7/F3MJlMzJ49mzfeeAOVqvPfdI0bN46ysjIATp8+3WX1rztUKhUqlYpLly4xZsyYW7qXEEIIIdyXubktcRvs3bN73KAtcbtkucQ3Ld/0+L2F6GskcevC4sWLefPNN9FoNBw/ftxpNWz9+vWcP3/e0Vly7dq1LFy4kAsXLhAfH4+vry96vd4xPzAwEK1W69hjptfriY2NpaqqiqysLPbv38/atWt77B1efvllPvvsM3Jzc9FoNJ12d3zmmWeYP38+Tz31FIMGDSIkJMTpvNdee43S0tJuPTslJYUpU6bcdOxCCCGEcH/tiVtP73GDtiMBAFkuKe4ICmct7l1h4sSJ9vaKT7uuuiyKnnfu3DlOnTpFeno63t7eLotDfu5CCCFE//GHc39g+eHl7MrYxaiAUT1678/qPiOtKI0X418kIyKjR+8thCsoFIpyu90+0dk12ePWT1y+fJnMzMxrxsaOHXtD+8vCw8MJDw/v6dCEEEIIcQdzLJXs4eMAAEL8Q/BR+lBhrrj+ZCHcnCRu/cTw4cM7NAgRQgghhHA1c7MZD4UH/p7+PX5v5QAlYwaPkSMBxB1B9rgJIYQQQoheY2oyMdhnsKOjdk8LHxzOObMkbqL/k8RNCCGEEEL0GnOzuVc6SrYLHxxOTWMNtc21vfYMIfoCSdyEEEIIIUSvMTWZej1xA6TqJvo9SdyEEEIIIUSvMTebe+Xw7XYRgREAss9N9HuSuHWhoaGBjIwMkpKSMBgMODs6YefOnY4z3EJDQ1m3bh0Wi4WMjAzUajVz5szBarUyd+5coqKiiIuLQ6/X09LSgkajIS4ujsTERBYtWtRpHO2fnTx5Munp6VgsFpYvX05sbCyBgYFoNBqOHDni9LOfffYZGo0GrVbLU089hd1u58KFC0yZMoXx48ezatUqAFpaWkhPTychIYE33njD8fmzZ8/yyCOPdPk9tb9HQkICjz/+OLW1tYSFhTmu/+xnP+Ott97q8h5CCCGE6J96e6lksF8w/p7+0llS9Htu01Vy5R//ypkv63r0nveNCOBX6eM6vb5582bi4uJYunQpOTk5lJWVER0dfc2ctLQ00tLSuHr1Kmq1mszMTIxGIxERERQVFZGZmcm2bdsAMBqNqNVq5s2bR3FxMQCFhYWMHDkSnU7X5fll7Z9dvXo1b7/9NqtXryYnJ4ecnBzHvZzJz8/nd7/7Hffeey+pqal88sknvPnmm7z44oskJCSgVqt5+umn2bx5MxMmTCAvL49p06ah1+v56quveP7557FYLNf9LtvfIycnh6NHj3LPPfdw5swZ7rvvPvbv38/zzz9/3XsIIYQQon9ptbdS21zbq4mbQqGQBiXijiAVty6EhIRQVFRERUUFBQUFHZK271qzZg3Z2dkEBQVx7NgxEhMTAVCr1Zw4ccIxz263Y7FY8PLycozZbDZqa2vx9fW9bkwmk6lb89q99NJLjmTw66+/5q677iIoKIiPP/6Y6upqmpubGTx4MCUlJTz66KMAJCYmUlZWxqBBg9i+fXu3n2W32zGbzfj6+pKSkkJxcTFfffUVCoWCu+++u9v3EUIIIUT/UH+1Hpvd1quJG0B4YFvi5mx1lBD9hdtU3LqqjPWW9PR0GhsbmT59OsnJyTQ2NlJR8c8yvFarZcWKFVRXV7Njxw4OHz4MQH19PQMHDgTAz8+Purq2SmFubi5XrlwhPT0drVbLqlWr0Ov1VFVVER0dTWhoaKex5Obm4u/vT2RkJLNnz77hd3nvvfcYN24cI0aMQKfT8frrr/PFF1+g1Wrx8PCgoaGBkJAQAIYMGUJ1dTXJycndvr9er0epVJKcnExiYiL+/v7k5eUxbNgwHn744RuOVwghhBDur/3w7d7c4wZtDUre//R9/tH4D4b6De3VZwnhKm6TuLlCRUUFOp2OGTNmkJ2djU6nY8OGDR3mLVu2jLy8PDw82r7OgIAAx/LChoYGAgICMJlMGI1GSktL8fb2dpxlUlhYSHBwMLNmzWLLli0YDAansbQvlbwZFy5c4Le//a1jSeXLL7/Mtm3bUCgULFq0iL179+Lv709jYyMqlQqLxYK//40dktm+VLJdVFQUZ8+e5U9/+hOPP/74TcUthBBCCPfWnrj1dsUtYnBbg5IKc4UkbqLfkqWSXSgoKKCoqAilUklkZCRNTU0d5pSXl1NTU0NqaqpjbNKkSZSUlABw6NAhYmJiHNcWLFjAxo0bsdlsjjFPT08CAgKor6/v8XcwmUzMnj2bN954A5VKBcDFixf5/PPPaWpq4qOPPkKhUDBhwgRKS0sBOH36NKNHj76l5yoUCmJjY/nDH/5w0wmnEEIIIdybuen2VNx+MPgHgHSWFP2bVNy6sHjxYrKysti0aRMqlYp33nmnw5z169dz/vx5NBoNADNnzmThwoUYDAbi4+OJiIhAr9ezZ88eAAIDA9FqtY69Y3q9HrvdjkqlIisri/3793PmzBkWLlzYI+/w8ssv89lnn5GbmwvAypUrWblyJRqNhpqaGn7yk5+g1Wr54Q9/yLRp0zh06BBnzpxh0qRJTu+3detWvLy8mDlz5nWfnZKSgtlsvmY/nxBCCCHuHKZmEwAqb1WvPifIN4ghPkM4X3u+V58jhCsp+somzokTJ9rLysquGeuqy6LoeV9++SWlpaWkpKQ4qnOuID93IYQQon9483/e5P+U/x+OzD6Cv9eNbcO4UfP3zKfJ2sTbaW/36nOE6E0KhaLcbrdPdHZNKm79xOXLl8nMzLxmbOzYseTn53f7HiNGjHB0lhRCCCGEuFXmZjMeAzwY6Dmw158VPjicD859QKu9lQEK2Q0k+h9J3PqJ4cOHO/bVCSGEEEL0BeZmM4HegY6mbL0pPDCcb6zfUNVQRYh/SK8/T4jbTX4dIYQQQggheoWpydTr+9vatXeWlAYlor+SxE0IIYQQQvQKc7O51ztKtmvvLFlhrrjOTCHckyRuQgghhBCiV5ibzb1+hlu7QV6DGD5wOOfMUnET/ZMkbkIIIYQQole073G7XX4w+AeyVFL0W5K4daGhoYGMjAySkpIwGAw4Ozph586daDQaNBoNoaGhrFu3DovFQkZGBmq1mjlz5mC1Wpk7dy5RUVHExcWh1+tpaWlBo9EQFxdHYmIiixYt6jSO5cuXExsbS2BgIBqNhiNHjmCz2XjqqaeYPHkyc+bMobW11elnL126xMiRIx0x1tTUADB//nzi4uJYvXq1Y+73x6xWK/fcc4/js5988onTZ7z55puEhYWRlJSEWq3mr3/9K7NmzWLv3r0AfPzxxyQnJ3fvSxdCCCFEv9Bqb8XcbL5te9ygbZ/bxdqLWFutt+2ZQtwu7tNVcve/wWXnicNNG/5jSH2508ubN28mLi6OpUuXkpOTQ1lZGdHR0dfMSUtLIy0tjatXr6JWq8nMzMRoNBIREUFRURGZmZls27YNAKPRiFqtZt68eRQXFwNQWFjIyJEj0el0nZ5ftnr1anJycsjJyXF8buvWrTQ3N3Po0CFeeOEFPvjgA6ZPn97hs8eOHeMXv/gFzzzzjGNsx44d2Gw2jhw5whNPPEFFRQWffPJJh7H6+npmz57Nb37zm+t+lfPnz2f58uWUlpayevVqdDode/fuZerUqezbt4+UlJTr3kMIIYQQ/Uf91Xpa7a23bY8btB0JcLX1Kp/Xf06YKuy2PVeI20Eqbl0ICQmhqKiIiooKCgoKOiRt37VmzRqys7MJCgri2LFjJCYmAqBWqzlx4oRjnt1ux2Kx4OXl5Riz2WzU1tbi6+vb7dj27NlDWloaALNmzWLo0KFO5x09epSCggIefPBBfv7znwNQUlLiOK/t4YcfprS01OnY0aNH+e///m9iYmKYP38+Vuv1f3tlMpnw9fUlJSWFffv2AVBcXCyJmxBCCHGHMTebAW7bHjdoOxIAkH1uol9yn4pbF5Wx3pKenk5jYyPTp08nOTmZxsZGKir+2alIq9WyYsUKqqur2bFjB4cPHwagvr6egQPbDpr08/Ojrq4OgNzcXK5cuUJ6ejparZZVq1ah1+upqqoiOjqa0NDQbsdWXV3NkCFDAHjwwQc7nZeamsovf/lL/Pz8eOihh/j4449paGggJKTtfJMhQ4bw0UcfOR2bMmUKxcXF3H333Tz++OPs2rWLn/70p06fs3HjRvbu3UtgYCBGo5ERI0Zgs9moqqrib3/7G+PHj+/2uwkhhBDC/ZmaTAC3teI2RjUGBQrOmc4xNXTqbXuuELeD+yRuLlBRUYFOp2PGjBlkZ2ej0+nYsGFDh3nLli0jLy8PD4+2rzMgIACLxQK07ZMLCAjAZDJhNBopLS3F29vbcRBlYWEhwcHBzJo1iy1btmAwGLoV23ef8cEHH2CxWMjOzu4wLz4+Hm9vbwCioqKoqKjA39+fxsZGACwWC62trU7H7r//fsdnJ06ceE3S+n3tSyW/a+rUqfz6178mPj7+thy8KYQQQoi+wxUVN18PX0YNGiVHAoh+SZZKdqGgoICioiKUSiWRkZE0NTV1mFNeXk5NTQ2pqamOsUmTJlFSUgLAoUOHiImJcVxbsGABGzduxGazOcY8PT0JCAigvr6+27ElJCQ4mn/s3buXwYOd/0sxJSWFqqoqvvnmGz788EMiIyOZMGECpaWlAJw+fZrRo0c7HTMYDJw+fRqbzcYHH3zAAw880O34AHQ6HevXr0en093Q54QQQgjh/torbrczcYO2fW6yVFL0R1Jx68LixYvJyspi06ZNqFQq3nnnnQ5z1q9fz/nz59FoNADMnDmThQsXYjAYiI+PJyIiAr1ez549ewAIDAxEq9Wyfft2APR6PXa7HZVKRVZWFvv37+fMmTMsXLiwy9ieeuopnnjiCdRqNWFhYUybNs3pvF/96lckJyfj5eXF008/zdixY7n77ruZPHkyX375Jbt37+bo0aMoFIoOY/fffz+PPfYYdrudn/70pzz00ENcuXKFpUuXUlBQcN3vT61W4+Pjw9SpslRBCCGEuNPUNtcCt3epJLTtczvwxQGabc14K71v67OF6E0KZy3uXWHixIn2srKya8Y667Iobp3JZGLv3r0kJiYyfPjwTsdcQX7uQgghhPtbU76GzWc2U55dflu3TOy+uJulB5fyfvr7jB0y9rY9V4ieoFAoyu12+0Rn16Ti1k9cvnyZzMzMa8bGjh1Lfn6+0/mBgYGOLpJdjQkhhBBC3Iz2w7dv9z738MH/7CwpiZvoTyRx6yeGDx/u2FcnhBBCCOFqpiYTKp/bd/h2u9EBo/FQeMg+N9HvdKs5iUKhCFYoFIe+/fM9CoWiRKFQ7FcoFP+paOOpUCj+qFAoDisUiie+nddhTAghhBBC3BnaK263m6fSk9Gq0ZwzSeIm+pfrJm4KhSIQeAsY+O3QAuAZu92uBUYBPwZygXK73Z4AzFQoFIM6GRNCCCGEEHcAc7P5tneUbBc+OFyOBBD9TncqbjZgFlAHYLfbf2G3289+ey0I+AegAbZ9O3YQmNjJmBBCCCGEuAOYm8y3vaNku/DB4VyyXOKblm9c8nwhesN1Eze73V5nt9trvz+uUChmAX+12+1f0laNu/TtpStAcCdj37/HUwqFokyhUJTV1NTc5CsIIYQQQoi+xNZqo/ZqLSrv27/HDdqOBAA4bz7vkucL0Rtu6gBuhUIxBvhXYMm3QxbA99s/+397X2dj17Db7f9pt9sn2u32iUOHDr2ZUHpVQ0MDGRkZJCUlYTAYcHZ0ws6dO9FoNGg0GkJDQ1m3bh0Wi4WMjAzUajVz5szBarUyd+5coqKiiIuLQ6/X09LSgkajIS4ujsTERBYtWtRpHMuXLyc2NpbAwEA0Gg1Hjhxx3K/92ZcvX3b62ZMnT5KQkEBiYiIrV64EwGw2k5iYSEJCArt37+50rLS0lPDwcDQaDVOmTOk0vvZYJk+eTHp6OvX19YSGhtLQ0ADA66+/7ni2EEIIIfq/+qv1tNpbXbLHDSBicASANCgR/coNd5X8ds/bO8AT36nElQNq4H3gAeBoJ2M37TfHf8P/XvnfW7lFBz8a8iNeiHmh0+ubN28mLi6OpUuXkpOTQ1lZGdHR0dfMSUtLIy0tjatXr6JWq8nMzMRoNBIREUFRURGZmZls29a2YtRoNKJWq5k3bx7FxcUAFBYWMnLkSHQ6Xafnl61evZqcnBxycnIcn8vPz3fcryvr16+nqKiIYcOGMW7cOJYsWcKKFSt44oknMBgMPPTQQ+h0Oqdjx48fx2g0kpqaet3vsj2W1atXs3XrVjQaDQcOHGDatGns27ePZcuWXfceQgghhOgfzM1mAAb7uGaPW4h/CN5Kb9nnJvqVm6m4/RtwD2D8trtkEm3NS1YqFIr/AO4DjnUy5lZCQkIoKiqioqKCgoKCDknbd61Zs4bs7GyCgoI4duwYiYmJAKjVak6cOOGYZ7fbsVgseHl5OcZsNhu1tbX4+vp2uO+tys/PZ9iwYbS0tGC1WvHz8+PgwYPMnDkTpVLJ2LFjqaysdDp29OhRVq1aRVRUFGvXru3W80wmE76+vqSkpFBcXIzNZuPjjz/u8rsTQgghRP/Snri5quKmHKBkjGqMLJUU/Uq3K252u13z7f9/AehQplIoFFNpq7CtsNvtNuDvTsZuWleVsd6Snp5OY2Mj06dPJzk5mcbGRioq/vmbG61Wy4oVK6iurmbHjh0cPnwYgPr6egYObGvC6efnR11dHQC5ublcuXKF9PR0tFotq1atQq/XU1VVRXR0NKGhoTcUX25uLiqViqFDh1JYWNjl3Ndee43HHnsMT09PPDw88Pf3B2DIkCFUV1c7HZs3bx5Tp07FarUyYcIEZs+eTVBQUKex+Pv7ExkZyezZs6mtreWVV17hxIkTxMTEoFQqb+jdhBBCCOG+TE0mAJd1lQSICIzg6Je3tOBLiD6lxw7g/rZJybbrjbmTiooKdDodM2bMIDs7G51Ox4YNGzrMW7ZsGXl5eXh4tH2dAQEBWCwWoG2fXEBAACaTCaPRSGlpKd7e3igUCqBtqWRwcDCzZs1iy5YtGAyGbsfXnaWSAMeOHWPXrl2OZZbfTaIsFgutra1Ox7RaLR4eHnh4eDiqcJ0lbt+P5a677sLLy4u3336blJSUbr+TEEIIIdyfq5dKQltnyf86/1/UNruuSYoQPemmmpPcKQoKCigqKkKpVBIZGUlTU1OHOeXl5dTU1FyzD2zSpEmUlJQAcOjQIWJiYhzXFixYwMaNG7HZ/lmA9PT0JCAggPr6+h5/h8rKSp599lm2bt2Kp6cnAOPGjaOsrAyA06dPExoa6nRMrVZjsViorq7m5MmThIeH39CzU1JSyM/Pl8RNCCGEuMO4eqkktCVuIA1KRP8hiVsXFi9ezJtvvolGo+H48eNOq2Hr16/n/Pnzju6Oa9euZeHChVy4cIH4+Hh8fX3R6/WO+YGBgWi1WrZv3w6AXq8nNjaWqqoqsrKy2L9/f7f3k+Xm5jqee+DAAadzXnjhBa5cuUJWVhYajYa//e1vPPPMM8yfP5+nnnqKQYMGERIS4nTsueeeIyoqCp1Ox6uvvopKpbqh+FJSUhg7diwhISHdmi+EEEKI/sHUbMJrgBe+Hj2/f7+7IgK/7SxpksRN9A8KZy3uXWHixIn29opPu866LIpbd+7cOU6dOkV6ejre3t6djrmC/NyFEEII97bi8AoOXzrMvkf3uSwGu91O/DvxpI1JY3nscpfFIcSNUCgU5Xa7faKzaz22x0241qlTp1iyZMk1Y0lJSZ2enxYeHt5h6aOzMSGEEEKIG2VqNrl0fxuAQqEgfHC4LJUU/YYkbv3E+PHjHfvqhBBCCCFcqba51qX729r9YPAPKP6sGLvd7mgMJ4S7kj1uQgghhBCiR5maXF9xg7Z9brXNtXzd9LWrQxHilkniJoQQQgghepS52ezSM9zatXeWrDBVXGemEH2fJG6iS3/96185dOjQNccXCCGEEEJ0xtZqo7a5tk8lbrLPTfQHkrh1oaGhgYyMDJKSkjAYDDjrwLlz505HS/7Q0FDWrVuHxWIhIyMDtVrNnDlzsFqtzJ07l6ioKOLi4tDr9bS0tKDRaIiLiyMxMZFFixZ1Gsfy5cuJjY0lMDAQjUbDkSNHHPdrf/bly5edfvbkyZMkJCSQmJh4TaOSAwcO8OSTTzr++eLFi0RHR5OYmMhHH30EwNtvv01eXh7vvfceTzzxRKfxhYWFodFoiI2NZenSpZw9e5aEhATH9enTp3d6XIEQQggh+pf6q/XYsRPo4/o9bkG+QQzxGSKJm+gXJHHrwubNm4mLi+PAgQN4e3vz/eMKANLS0igpKeHDDz8kODiYzMxMjEYjERERlJaW0tzczLZt2wAwGo0cOXIEf39/iouLASgsLOTgwYN8+umnnD171mkcq1ev5t1332XChAmUlJQQFxfnuF9JSQklJSUMHz7c6WfXr19PUVERBw8eZNu2bdTW1nL06FFWrlxJS0uLY97ixYt59dVX2bVrF7/4xS8AqKqq4t1332Xt2rWOZM4ZpVJJSUkJR48e5aOPPmLAgAFUV1dTV1dHa2sr5eXlxMfHd+MbF0IIIYS7MzWbAPpExQ3aqm5ylpvoD9ymq+TlX/+a5rP/26P39L73Rwz/+c87vR4SEsJbb71FRkYGBQUFXd5rzZo1ZGdnExQUxLFjx8jJyQFArVZz4sQJxzy73Y7FYsHLy8sxZrPZqK2txde35w+pzM/PB6ClpQWr1Yqfnx+jRo2ioKCAF1980THvzJkzaDQaAAYMGEBLSwv/+q//Sm1tLZs2bWLKlCnXfZbVaqWhoQEfHx+0Wi0lJSXcfffdjB8/Hk9Pzx5/NyGEEEL0PeZmM9C3ErcPzn1Aq72VAQqpWQj35TaJmyukp6fT2NjI9OnTSU5OprGxkYqKf25u1Wq1rFixgurqanbs2MHhw4cBqK+vZ+DAgQD4+flRV1cHQG5uLleuXCE9PR2tVsuqVavQ6/VUVVURHR1NaGjoDcWXm5uLSqVi6NChFBYWdjn3tdde47HHHsPT05OQkBAqKyuvuT548D//5apSqfj6668ZPnw4Fy9e5I9//COPPfZYp/e22WxoNBqsVisGg4HQ0FB0Oh3FxcWMGDECnU53Q+8lhBBCCPdlavq24tYHukoChAeG8431G6oaqgjxD3F1OELcNLdJ3LqqjPWWiooKdDodM2bMIDs7G51Ox4YNGzrMW7ZsGXl5eXh4tH2dAQEBWCwWoG2fXEBAACaTCaPRSGlpKd7e3o6zRAoLCwkODmbWrFls2bIFg8HQ7fiMRiNqtfq6844dO8auXbscyzOdGTDgn7+BslgstLa2Am3nw+3du5f77ruP+fPnO/1s+1LJ75oyZQp5eXkEBwc7qn5CCCGE6P9qm2sB+sQ5bvCdBiWmc5K4Cbcm9eIuFBQUUFRUhFKpJDIykqampg5zysvLqampITU11TE2adIkRyJz6NAhYmJiHNcWLFjAxo0br+nS6OnpSUBAAPX19T3+DpWVlTz77LNs3bq1y+WKgwcP5vLly9jtds6fP8/QoUNRq9WYTCaam5vx9va+oeeqVCpUKhWXLl1izJgxt/oaQgghhHATfW2P2w8G/wCACrMcCSDcm9tU3Fxh8eLFZGVlsWnTJlQqFe+8806HOevXr+f8+fOO/WEzZ85k4cKFGAwG4uPjiYiIQK/Xs2fPHgACAwPRarVs374dAL1ej91uR6VSkZWVxf79+zlz5gwLFy68bnztSyUBVq5cSVJSUoc5L7zwAleuXCErKwto2/M2duzYDvP+5V/+hYyMDEJDQ0lOTsbT05Of//znPPTQQ/j6+vLSSy8BbUsuY2JiulXpS0lJobq6+rrzhBBCCNF/mJvMeCu98fXo+b37NyPAK4Bgv2DOm8+7OhQhbonCWYt7V5g4caL9+10bz549y7333uuiiO48p0+f5u9//zs/+clPrlk6ebvJz10IIYRwX788/Ev+8uVf2Kff5+pQHJ4ufpqvG7+mML3rngBCuJpCoSi32+0TnV2Tils/cerUKZYsWXLNWFJS0jVnt13PAw88wAMPPNDToQkhhBDiDmJuMveZ/W3tIgZHcKLqBNZWKx4D5D9/hXuSv7n9xPjx4zs0CBFCCCGEuN3MzeY+01GyXfjgcK62XuXz+s8JU4W5Ohwhboo0JxFCCCGEED3G3Nz3Km7hgd92ljTLQdzCfUniJoQQQggheoyp2YTKW+XqMK4xRjUGBQr+/NmfabQ2ujocIW6KJG5CCCGEEKJH2Fpt1DXXEejTtypuvh6+pIal8scLf+Th9x/m/536f46DwoVwF5K43aEuXLjAn//8Z5qbm10dihBCCCH6ibqrddix95kz3L7rN4m/4fepv2f8sPH87vTvePj9h3np6Et8Xv+5q0MTolskcetCQ0MDGRkZJCUlYTAYcHZ0ws6dO9FoNGg0GkJDQ1m3bh0Wi4WMjAzUajVz5szBarUyd+5coqKiiIuLQ6/X09LSgkajIS4ujsTERBYtWtRpHMuXLyc2NpbAwEA0Gg1Hjhxx3K/92ZcvX3b62ZMnT5KQkEBiYqKjw+SBAwd45pln+PDDD5k2bRoAZrOZxMREEhIS2L17t+PzBw4c4Mknn+zyewoLC0Oj0RAbG8vSpUs5e/YsCQkJjuvTp0/nwIEDXd5DCCGEEO6v/fDtvrbHrV3UsCiMWiN/eOQPpIal8n7F+/yk6Cc8f+B5znx9xtXhCdElSdy6sHnzZuLi4jhw4ADe3t58/5w5gLS0NEpKSvjwww8JDg4mMzMTo9FIREQEpaWlNDc3s23bNgCMRiNHjhzB39+f4uJiAAoLCzl48CCffvopZ8+edRrH6tWreffdd5kwYQIlJSXExcU57ldSUkJJSQnDhw93+tn169dTVFTEwYMH2bZtG7VC/BaXAAAgAElEQVS1tZw9e5Zt27bx7//+79TW1tLc3MyKFSt44oknOHjwIK+88gp2u52jR4+ycuVKWlpauvyelEolJSUlHD16lI8++ogBAwZQXV1NXV0dra2tlJeXEx8f3+3vXQghhBDuydxkBuiTFbfvGjN4DC8mvMieGXuYM24OpZdKmfXfs3jywyf5y6W/OP1lvRCu5jbHARza9in/+NzSo/e8a5Q/kx/9YafXQ0JCeOutt8jIyKCgoKDLe61Zs4bs7GyCgoI4duwYOTk5AKjVak6cOOGYZ7fbsVgseHl5OcZsNhu1tbX4+vre4ht1lJ+fD0BLSwtWqxU/Pz+efvppGhsb2bp1K2FhYXh7e3Pw4EF+/etfo1QqGTt2LJWVlYwaNYqCggJefPHFbj3LarXS0NCAj48PWq2WkpIS7r77bsaPH4+np2ePv5sQQggh+pb2iltfOw6gM8P8hvGzCT/jyR8/yfufvs+WM1tYULyAsYFjmRc5j5TRKXLum+gz5G9iF9LT02lsbGT69OkkJyfT2NhIRUWF47pWq2XFihVUV1ezY8cODh8+DEB9fT0DBw4EwM/Pj7q6OgByc3O5cuUK6enpaLVaVq1ahV6vp6qqiujoaEJDQ28ovtzcXFQqFUOHDqWwsLDLua+99hqPPfaYI4Gqrq7m/fffZ9y4cQB4eHjg7+8PwJAhQ6iuriY2NpbKysrrxmGz2dBoNFitVgwGA6Ghoeh0OoqLixkxYgQ6ne6G3ksIIYQQ7qm2uRbou0slOzPIaxDzIueRdW8WOy/s5M2/vsm/Hfo3Xv/odR4f9zgZ4Rn4efq5Okxxh3ObxK2rylhvqaioQKfTMWPGDLKzs9HpdGzYsKHDvGXLlpGXl4eHR9vXGRAQgMXSVh1saGggICAAk8mE0WiktLQUb29vFAoF0LZUMjg4mFmzZrFlyxYMBkO34zMajajV6uvOO3bsGLt27XIszwQYPXo0O3bsYPLkyVy+fBmlUum4ZrFYaG1t7XYc7Uslv2vKlCnk5eURHBzsqPoJIYQQon9r79ToLhW37/NSepERkcEj4Y9w8IuDbPqfTbx8/GV+d/p3zP7RbGb/aDZDfIa4Okxxh5I9bl0oKCigqKgIpVJJZGQkTU1NHeaUl5dTU1NDamqqY2zSpEmORObQoUPExMQ4ri1YsICNGzdis9kcY56engQEBFBfX9/j71BZWcmzzz7L1q1bHdW2Rx55hHPnztHa2kpTUxMDBw5k3Lhxjj18p0+fvuHq3/epVCpUKhWXLl1izJgxt/weQgghhOj7zM1mvJXe+Hr0/PaP22mAYgCaURreSn2LzambmTBsAvmn83n4/YdZfXQ1n9dJJ0px+7lNxc0VFi9eTFZWFps2bUKlUvHOO+90mLN+/XrOnz+PRqMBYObMmSxcuBCDwUB8fDwRERHo9Xr27NkDQGBgIFqtlu3btwOg1+ux2+2oVCqysrLYv38/Z86cYeHChdeNr32pJMDKlStJSkrqMOeFF17gypUrZGVlAW173pYvX+5YNvn0008zaNAgnnnmGebPn8+kSZMYNGgQISEhTp/52muvERMT061KX0pKCtXV1dedJ4QQQoj+wdRk6vONSW7U+GHj+Q/tf3Ch9gK//+vv2VGxg8JPC5kaOpV54+Yx7q5xrg5R3CEUfaVrzsSJE+3f79p49uxZ7r33XhdFdOc5d+4cp06dIj09HW9vb5fFIT93IYQQwj3l7svl8jeXKUzveu+9O6v5poa3z77Ntr9to76lnknDJzEvch7xI+IdW2GEuFkKhaLcbrdPdHZNKm79xKlTp1iyZMk1Y0lJSY6z27ojPDyc8PDwng5NCCGEEHcIU3P/q7h931C/oSyZsIScH+ewvWI7vz/ze54ufpofBv7Q0YnSc4B00xY9TxK3fmL8+PEdGoQIIYQQQtxO5mYzdw+829Vh3Bb+Xv7MGTeHx370GLsu7mLT/2xi2aFlvP7R6zw38TlSRqe4OkTRz0hzEiGEEEII0SP64x636/FUevJI+CPseGQH66asY5DXIH71l1/RZO3Y1E6IWyGJmxBCCCGEuGXWViv1V+sJ9HGvM9x6ygDFABJHJvKvE/+VhpYGDn5x0NUhiX5GEjchhBBCCHHL6q7WYcd+x1Xcvi9meAxBPkHsvrjb1aGIfkYSNyGEEEIIccvMTWaAO7bi1k45QElqWCoHvzhI3dU6V4cj+hFJ3IQQQgghxC0zNZsAUHmrXByJ66WGpXK19Sr7/r7P1aGIfkQSty40NDSQkZFBUlISBoMBZ2fe7dy5E41Gg0ajITQ0lHXr1mGxWMjIyECtVjNnzhysVitz584lKiqKuLg49Ho9LS0taDQa4uLiSExMZNGiRZ3GsXz5cmJjYwkMDESj0XDkyBHH/dqfffnyZaefLS0tJTw8HI1Gw5QpUxzjZ8+e5ZFHHnH8s9lsJjExkYSEBHbvbivtnzx5koSEBBITE7s8VqD9PRISEnj88cepra0lLCzMcf1nP/sZb731VudftBBCCCHcnrn524qb951dcQP48V0/ZqT/SFkuKXqU2xwH8Oc3/5Ov/n6hR+85LHQMyXOf6vT65s2biYuLY+nSpeTk5FBWVkZ0dPQ1c9LS0khLS+Pq1auo1WoyMzMxGo1ERERQVFREZmYm27ZtA8BoNKJWq5k3bx7FxcUAFBYWMnLkSHQ6XacHT69evZqcnBxycnIcn8vPz3fcryvHjx/HaDSSmprqGDt//jzPP/88FovFMbZixQqeeOIJDAYDDz30EDqdjvXr11NUVMSwYcMYN24cS5YsQaVy/lu09vfIycnh6NGj3HPPPZw5c4b77ruP/fv38/zzz3cZpxBCCCHcmyyV/CeFQsG0MdMo+KSAfzT+g7t873J1SKIfkIpbF0JCQigqKqKiooKCgoIOSdt3rVmzhuzsbIKCgjh27BiJiYkAqNVqTpw44Zhnt9uxWCx4eXk5xmw2G7W1tfj6+vb4Oxw9epRVq1YRFRXF2rVrARg0aBDbt2+/Zt7BgweZOXMmSqWSsWPHUllZSX5+PsOGDaOlpQWr1Yqfn1+Xz7Lb7ZjNZnx9fUlJSaG4uJivvvoKhULB3XffGWe6CCGEEHcqWSp5rWlh02i1t7Knco+rQxH9hNtU3LqqjPWW9PR0GhsbmT59OsnJyTQ2NlJRUeG4rtVqWbFiBdXV1ezYsYPDhw8DUF9fz8CBAwHw8/Ojrq5tY2pubi5XrlwhPT0drVbLqlWr0Ov1VFVVER0dTWho6A3Fl5ubi0qlYujQoRQWFjqdM2/ePKZOnYrVamXChAnMnj2bYcOGdZjn4eGBv78/AEOGDKG6utqx3PG1117jsccew9PTs9NY9Ho9SqWS5ORkEhMT8ff3Jy8vj2HDhvHwww/f0HsJIYQQwv2Ym8z4KH3w9ej5X0S7ox8M/gFjA8ey6+Iusu7NcnU4oh9wm8TNFSoqKtDpdMyYMYPs7Gx0Oh0bNmzoMG/ZsmXk5eXh4dH2dQYEBDiWITY0NBAQEIDJZMJoNFJaWoq3tzcKhQJoW2IYHBzMrFmz2LJlCwaDodvxdWeppFarxcPDAw8PD0clLSgoqMM8pVLp+LPFYqG1tRWAY8eOsWvXLscSzc60L5VsFxUVxdmzZ/nTn/7E448/3u13EkIIIYR7MjWbGOxzZx8F8H2pYan834/+L5/Xf86oQaNcHY5wc7JUsgsFBQUUFRWhVCqJjIykqampw5zy8nJqamqu2UM2adIkSkpKADh06BAxMTGOawsWLGDjxo3YbDbHmKenJwEBAdTX1/do/Ha7HbVajcViobq6mpMnTxIeHu507rhx4ygrKwPg9OnThIaGUllZybPPPsvWrVu7rLY5o1AoiI2N5Q9/+MN1k0shhBBCuL/a5lppTPI9qWFt/30oTUpET5CKWxcWL15MVlYWmzZtQqVS8c4773SYs379es6fP49GowFg5syZLFy4EIPBQHx8PBEREej1evbsaVvfHBgYiFardewx0+v12O12VCoVWVlZ7N+/nzNnzrBw4cLrxte+VBJg5cqVJCUlXXNdoVDw3HPPERUVhb+/P6+++mqnzUWeeeYZ5s+fz6RJkxg0aBAhISHMmjWLK1eukJXVVt7Pz8+nvLwcLy8vZs6ced34UlJSMJvN1+znE0IIIUT/ZGo23fGHb3/fCP8RPDjsQXZd2MWTP37SseJKiJuhcNbi3hUmTpxob6/4tOusy6LoHefOnePUqVOkp6fj7e3tsjjk5y6EEEK4n7QdaYwLGscrSa+4OpQ+5d3/fZeXjr3E++nvM3bIWFeHI/o4hUJRbrfbJzq7JhW3fuLUqVMsWbLkmrGkpKQuz1/7vvDw8E6XUgohhBBCdEX2uDn38OiHefn4y+y+uFsSN3FLJHHrJ8aPH+/YVyeEEEIIcTtZW63UX62XPW5ODPEZQtyIOHZf3M2iBxcxQCEtJsTNkb85QgghhBDiltQ21wJIxa0T08Km8WXDl5yuOe3qUIQbk8RNCCGEEELcEnOzGUCak3RCe48Wb6U3uy7scnUowo1J4iaEEEIIIW6JqckESOLWmYGeA9GM0vDh3z+kpbXF1eEINyWJmxBCCCGEuCXtSyUDfWSPW2dSw1K50nSFY1XHXB2KcFOSuHWhoaGBjIwMkpKSMBgMODs6YefOnWg0GjQaDaGhoaxbtw6LxUJGRgZqtZo5c+ZgtVqZO3cuUVFRxMXFodfraWlpQaPREBcXR2JiIosWLeo0juXLlxMbG0tgYCAajYYjR4447tf+7MuXLzv9bGlpKeHh4Wg0GqZMmQLAZ599hkajQavV8tRTT2G322lpaSE9PZ2EhATeeOONTuc50x7L5MmTSU9Pp76+ntDQUBoaGgB4/fXXb6i7pRBCCCHci6lZKm7XMzlkMoM8B8lh3OKmuU1XSfMfz3P1y4YevafXiIEMTv9Bp9c3b95MXFwcS5cuJScnh7KyMqKjo6+Zk5aWRlpaGlevXkWtVpOZmYnRaCQiIoKioiIyMzPZtm0bAEajEbVazbx58yguLgagsLCQkSNHotPpOj2/bPXq1eTk5JCTk+P4XH5+vuN+XTl+/DhGo5HU1FTHWH5+Pr/73e+49957SU1N5ZNPPqG4uJgJEyaQl5fHtGnT0Ov1Tufdf//9Tp/THsvq1avZunUrGo2GAwcOMG3aNPbt28eyZcu6jFMIIYQQ7kv2uF2fl9KLqaOn8qeLf+KXsb/Ex8PH1SEJNyMVty6EhIRQVFRERUUFBQUFHZK271qzZg3Z2dkEBQVx7NgxEhMTAVCr1Zw4ccIxz263Y7FY8PLycozZbDZqa2vx9fXt8Xc4evQoq1atIioqirVr1wLw0ksvORLEr7/+mrvuuouSkhIeffRRABITEykrK3M673pMJhO+vr6kpKRQXFyMzWbj448/7vK7E0IIIYR7MzWZ8PXwlWTkOlLDUvnG+g0Hvjjg6lCEG3KbiltXlbHekp6eTmNjI9OnTyc5OZnGxkYqKioc17VaLStWrKC6upodO3Zw+PBhAOrr6xk4cCAAfn5+1NXVAZCbm8uVK1dIT09Hq9WyatUq9Ho9VVVVREdHExoaekPx5ebmolKpGDp0KIWFhU7nzJs3j6lTp2K1WpkwYQKzZ88mKCgIgPfee49x48YxYsQIGhoaCAkJAWDIkCFUV1c77vHdeV3F4u/vT2RkJLNnz6a2tpZXXnmFEydOEBMTg1KpvKF3E0IIIYT7MDebpdrWDdHB0dzlexe7L+4mZXSKq8MRbsZtEjdXqKioQKfTMWPGDLKzs9HpdGzYsKHDvGXLlpGXl4eHR9vXGRAQgMViAdr2yQUEBGAymTAajZSWluLt7Y1CoQDalkoGBwcza9YstmzZgsFg6HZ83VkqqdVq8fDwwMPDg7Fjx1JZWUlQUBAXLlzgt7/9rWPppb+/P42NjahUKiwWC/7+/gAd5nU3lrvuugsvLy/efvttUlLkX0xCCCFEfyaJW/coByjRjdbx3t/eo+5qHQFeAa4OSbgRWSrZhYKCAoqKilAqlURGRtLU1NRhTnl5OTU1NdfsIZs0aRIlJSUAHDp0iJiYGMe1BQsWsHHjRmw2m2PM09OTgIAA6uvrezR+u92OWq3GYrFQXV3NyZMnCQ8Px2QyMXv2bN544w1UKhUAEyZMoLS0FIDTp08zevRop/NuREpKCvn5+ZK4CSGEEP2cucksHSW7aVrYNFpaW9j3932uDkW4Gam4dWHx4sVkZWWxadMmVCoV77zzToc569ev5/z582g0GgBmzpzJwoULMRgMxMfHExERgV6vZ8+ePQAEBgai1WrZvn07AHq9HrvdjkqlIisri/3793PmzBkWLlx43fjal0oCrFy5kqSkpGuuKxQKnnvuOaKiovD39+fVV19FpVLxwgsv8Nlnn5Gbm+v47Jw5c5g2bRqHDh3izJkzTJo0iZ///Ocd5tlstm7Hl5KSwgcffOBYgimEEEKI/snUbCJkkPzvfXdE3hXJqEGj2HVxFxkRGa4OR7gRRWct3m+3iRMn2svKyq4Z66zLougdX375JaWlpaSkpNxUha2nyM9dCCGEcC/x78STPiadZZOki3R3GE8aKfikgOKZxQz1G+rqcEQfolAoyu12+0Rn12SpZD9x6tQpx5lu7f/3q1/96obuMWLECB599FGXJm1CCCGEcC8trS3UX61nsI/sceuutLA0Wu2t7Knc4+pQhBuRpZL9xPjx4x376oQQQgghbpfa5loAAr1lj1t3jRk8hh8N+RG7L+4m+75sV4cj3IRU3IQQQgghxE0zN8nh2zcjNSyVj//xMZ/Xfe7qUISbkMRNCCGEEELcNHPzt4mbLJW8Iamj2zqS767c7eJIhLuQxE0IIYQQQty09sRNlkremLv97+bBYQ+y88JO+kqzQNG3SeImhBBCCCFumqnZBMhSyZsxLWwaF2ov8KnpU1eHItyAJG5daGhoICMjg6SkJAwGg9PfhuzcudPRxTE0NJR169ZhsVjIyMhArVYzZ84crFYrc+fOJSoqiri4OPR6PS0tLWg0GuLi4khMTGTRokWdxrF8+XJiY2MJDAxEo9Fw5MgRx/3an3358mWnn927d6/jOe3n0JnNZhITE0lISGD37t2djgEcOHCAJ598ssvvKSwsDI1GQ2xsLEuXLuXs2bMkJCQ4rk+fPp0DBw50eQ8hhBBCuCfHHjdZKnnDHh79MB4KD3Zd3OXqUIQbcJuukrt37+40OblZw4cPJzU1tdPrmzdvJi4ujqVLl5KTk0NZWRnR0dHXzElLSyMtLY2rV6+iVqvJzMzEaDQSERFBUVERmZmZbNu2DQCj0YharWbevHkUFxcDUFhYyMiRI9HpdJ2eX7Z69WpycnLIyclxfC4/P99xv87YbDaee+45Dh8+jKenJw888AAZGRmsWLGCJ554AoPBwEMPPYROp3M6duzYMVauXMk999zT5feoVCodHS0feugh5s+fT3V1NXV1dfj7+1NeXk58fHyX9xBCCCGEezI1m/D18MVb6e3qUNxOoE8gcSPi2H1xN4sfXMwAhdRUROfkb0cXQkJCKCoqoqKigoKCgg5J23etWbOG7OxsgoKCOHbsGImJiQCo1WpOnDjhmGe327FYLHh5eTnGbDYbtbW1+Pr69mj89fX1+Pv7M2jQIHx8fPD29qaxsZGDBw8yc+ZMlEolY8eOpbKy0unYqFGjKCgo6PbzrFYrDQ0N+Pj4oNVqKSkpoby8nPHjx+Pp6dmj7yaEEEKIvqG2uVb2t92C1LBUqhqqOPXVKVeHIvo4t6m4dVUZ6y3p6ek0NjYyffp0kpOTaWxspKKiwnFdq9WyYsUKqqur2bFjB4cPHwbaEqaBAwcC4OfnR11dHQC5ublcuXKF9PR0tFotq1atQq/XU1VVRXR0NKGhoTcUX25uLiqViqFDh1JYWNjh+uDBg1GpVLz77rv84x//YNiwYQQGBuLh4YG/vz8AQ4YMobq62ulYbGwslZWV143DZrOh0WiwWq0YDAZCQ0PR6XQUFxczYsQIdDrdDb2XEEIIIdyHqckkyyRvgfYeLT5KH3Zd3MWDwQ+6OhzRh7lN4uYKFRUV6HQ6ZsyYQXZ2Njqdjg0bNnSYt2zZMvLy8vDwaPs6AwICsFgsQNs+uYCAAEwmE0ajkdLSUry9vVEoFEDbUsng4GBmzZrFli1bMBgM3Y7vekslAT744AP27dvH8uXL2bRpE9C2tLGdxWKhtbXV6Vh3fXepZLspU6aQl5dHcHAw+fn53b6XEEIIIdyLudksjUluwUDPgWhGafiw8kNeiHkBzwGySkk4J0slu1BQUEBRURFKpZLIyEiampo6zCkvL6empuaaiuCkSZMcicyhQ4eIiYlxXFuwYAEbN27EZrM5xjw9PQkICKC+vr7H38Hb25u77rqL+++/n8mTJwMwbtw4ysrKADh9+jShoaFOx26FSqVCpVJx6dIlxowZc2svIYQQQog+y9RkksTtFqWGpWJqNnH0y6OuDkX0YZK4dWHx4sW8+eabaDQajh8/7rQatn79es6fP+/o7rh27VoWLlzIhQsXiI+Px9fXF71e75gfGBiIVqtl+/btAOj1emJjY6mqqiIrK4v9+/ezdu3absWXm5vreG5XXRuXL1/Oq6++6vjnZ555hvnz5/PUU08xaNAgQkJCnI4589prr1FaWtqt+FJSUpgyZUq35gohhBDCPdU21xLoI3vcboU6RM0gr0HsviiHcYvOKfrKgX8TJ060t1d82nXWZVHcunPnznHq1CnS09Px9vbudMwV5OcuhBBCuIeW1hYe3Pwg/zL+X3j6gaddHY5by/tLHrsv7qZkVgm+Hj3bsE64D4VCUW632yc6uyZ73PqJU6dOsWTJkmvGkpKSWLlypdP54eHhhIeHX3dMCCGEEKIztc21gBy+3RNSw1LZXrGdA18cQDdaGruJjvp84ma32x2NPETnxo8f36FBiDvqKxVgIYQQQlyfqckEyOHbPWFi8ESG+g5l94XdkrgJp/r0HjcfHx++/vpr+Y/5O4Tdbufrr7/Gx8fH1aEIIYQQohvMzWYAOcetBygHKEkZncKhS4cclUwhvqtPV9xGjhzJF198QU1NjatDEbeJj48PI0eOdHUYQgghhOiG9sRNlkr2jLQxaWw5u4V9n+1jesR0V4cj+pg+nbh5enoSFhbm6jCEEEIIIYQT7UslpatkzxgXNI57Bt3Drou7JHETHfTppZJCCCGEEKLvkopbz1IoFKSGpXK86jg138iKM3EtSdyEEEIIIcRNMTeb8fPww0vp5epQ+o1pYdOwY+dPlX9ydSiij5HETQghhBBC3BRzk1mWSfawMYPHcO+Qe+UwbtGBJG5CCCGEEOKmmJpNskyyF6SGpfLJPz7hs7rPXB2K6EMkcRNCCCGEEDfF3GSWxK0XpIalAkjVTVxDEjchhBBCCHFTzM1mOXy7FwwfOJwJwRPYeXGnnGcsHCRxE0IIIYQQN8XcbJbDt3vJtLBpXKy9yN9Mf3N1KKKPkMRNCCGEEELcsBZbC5YWiyyV7CVTQ6fiofBg18Vdrg5F9BGSuAkhhBBCiBsmZ7j1rkCfQOJD4tl9cTet9lZXhyP6AEnchBBCCCHEDXMkbrLHrdekhqVyueEyJ7866epQRB8giZsQQgghhLhh7Ymb7HHrPdpRWnyUPi7vLtnS2uLS54s2krgJIYQQQogbZmoyAVJx601+nn4kj0pmT+UelyRPjdZGXjnxCjFbYjhadfS2P19cSxI3IYQQQghxw2SP2+2RGpaKudnMkS+P3NbnflT9Efo/6tl8ZjPKAUq2nt16W58vOpLETQghhBBC3DBHxU0St16lDlET4BVw25ZLNlob+c3x3zD3T3OxtlopeLiA7HuzOfjFQWq+qbktMQjnJHETQgghhBA3zNxsZqDnQLyUXq4OpV/zVHoyNXQq+z7bR6O1sVef9VH1R8z8r5lsObuFR8c+yo6f7mDS3ZPI+P/s3Xl4W/WVN/DvlSVvkuLdli1lt0M2J8FJyCIDZWlpWggk0AHa0ham+7AXCl2n7TBtocwMpWU6bWdaoAsvSxJKoGXf4jgLsUns7M4eS7Zs2ZJtSZas5b5/KNcoiRNbtqR7r/T9PE8fgmzde6DB0bnnd86pWYOwGMbfDv8tqfen82PiRkRERERxcwfcrLalyKemfwqDoUG8d/K9pFw/tsoWFsP4v0/8H76//PvI1+UDAKZOmoqlpqVY37aeqwlkxMSNiIiIiOLmCriYuKXI4orFKM8rT8oy7iZHE65/6frTqmwXVV501vetrVmLkwMnsaNzR8JjoLFh4kZEREREcXP73ZwomSJZmixcNf0qbLJtQl+gLyHXlKpst756KyJi5Kwq25munHIljNlGrGtbl5D7U/yYuBERERFR3NwBN3e4pdCnp38aoUgIbx5/c8LXiq2y3XjBjeesssXK1ebi6hlX483jbyYseaT4MHEjIiIiorixxy215pbMxdRJUyc0XdIX9OHn238+XGX7w1V/wPeWf++cVbYzXV9zPYYiQ3j5yMvjjoHGj4kbEREREcVlKDwEb9DLxC2FBEHAqumrsL1zO7p8XXG/f0fnDtyw8Qb8Zd9fcNPsm7B+9XosNS2N6xoXFF+A+SXzsa5tHURRjDsGmhgmbkREREQUF2n5dlEuj0qm0qrpqyBCxGvHXhvze4arbK/dClEU8Yer/oDvLvvumKtsZ1o7ay3aXG3Y7dw9rvfT+DFxIyIiIqK4SIkbK26pNaNgBuYUz8Hfj4xtumRsle3m2Tdj3ep1cVfZzrRq2irkafM4pEQGTNyIiIiIKC5uPytucvnU9E9hd89uHO8/fs7v8QV9+Nm2nyWsyhbLkG3AVdOuwj+O/gO+oG/C16OxY+JGRERERHFxBVwAWHGTwyenfxIChHMOKfmg8wNc/9L1+Ov+v+Kzsz+bkCrbma6vuR6+kCR5nzwAACAASURBVC+uI5s0cUzciIiIiCguUsWNiVvqmfQmLK5YjFeOvHLagBCpynbba7cBAP5w1R/wnWXfSUiV7UwLyxZiZsFMHpdMMSZuRERERBQX9rjJa9X0VTjWfwz7e/cDOL3K9rk5n0tKlS2WIAhYW7MWu7p34ZDrUNLuQ6dj4kZEREREcXEH3DDoDNBl6eQOJSN9YuonoBW0WNe2Dj/d9tPhKtsfr/ojHrzowaRU2c50zcxroNVoWXVLIa3cARARERGRurgCLlbbZFSYWwir2YpnDzwLAPjcnM/hzgvvTEnCJinKLcIVU67AxiMbcc/ie5CdlZ2ye2cqVtyIiIiIKC5uv5uJm8y+OO+LWFyxOKVVtjOtrVmLvkAf3j7xdsrvnYmYuBERERFRXNwBNwpzmbjJaalpKZ785JNYYloiWwzLK5ejSl/F45IpwsSNiIiIiOLiDrhRlMMdbplOI2iwpmYNtnZsRftAu9zhpD0mbkREREQUF5ffxYobAQCuq74OGkGDDYc2yB1K2mPiRkRERERjNhQegi/kY48bAYjulas31+PFthcRioTkDietMXEjIiIiojHjDjc609qatega7MJm22a5Q0lrTNyIiIiIaMxcfheA6Dh4IgC4xHIJSnJLOKQkyZi4EREREdGYseJGZ9JpdLi2+lq83/4+un3dcoeTtpi4EREREdGYuQLRihsTN4q1tmYtwmIYfzv8N7lDSVtM3IiIiIhozNz+aMWNRyUp1tRJU7HUtBTr29ZDFEW5w0lLTNyIiIiIaMyko5IFOQUyR0JKs7ZmLU4OnMQHnR/IHUpaYuJGRERERGPmDrhh1Bmh0+jkDoUU5sopV8KYbeSQkiRh4kZEREREY+byu1htoxHlanNx9Yyr8ebxN9EX6JM7nLTDxI2ISIFCkRBu+fstePP4m3KHQkR0GnfAzf42Oqfra67HUGQILx95We5Q0g4TNyIiBTrQewA7u3dii32L3KEQEZ3GHXBzoiSd0wXFF2BeyTysa1vHISUJxsSNiEiBmhxNAACbxyZzJEREp3P7WXGj87t+1vVoc7VhT88euUNJK0zciIgUiIkbESmVK+BixY3Oa9W0VcjT5uGFgy/IHUpaYeJGRKQwETGC5q5mANHELSJGZI6IiCgqEA5gMDTIxI3Oy5BtwFXTrsI/jv4DvqBP7nDSBhM3IiKFOdp3FO6AGwtKFyAYCaLL1yV3SEREAD5avl2Yy8SNzu/6muvhC/nw2rHX5A4lbTBxIyJSGOmY5OqZqwEA7QPtcoZDRDRMWr5dlMMeNzq/hWULMaNgBne6JRATNyIihWlyNKEsrwzLq5YDYJ8bESmHK+ACAB6VpFEJgoC1NWuxq3sXDrkOyR1OWmDiRkSkIKIoYodjB+oq6lClr4IAAe0eVtyISBmGj0oycaMxuGbmNdBqtFh/aL3coaQFJm5ERApi89jQ5evC4orF0GXpYNKbYBtgxY2IlEE6KskeNxqL4txiXDHlCmw8vBFD4SG5w1E9Jm5ERAoiTZNcXLEYAGA2mHlUkogUQzoqWZBTIHMkpBZra9bCHXDj7RNvyx2K6jFxIyJSkCZHEyZlT0J1YTUAwGK0cDgJESmG2++GMdsInUYndyikEssrl6NKX8UhJQnAxI2ISEGaHc2oK6+DRoj+eDYbzOga7EIgHJA5MiIiLt+m+GkEDdbUrMHWjq18EDlBTNyIiBTCOejEsf5jqKuoG37NbDAD4GRJIlKGvkAfVwFQ3K6rvg4aQYMNhzbIHYqqMXEjIlIIaX+b1N8GAJONkwGAA0qISBFcfhcHk1DcTHoTrFVWvHjoRYQiIbnDUa0xJW6CIFQIgrDp1K91giBsFARhsyAIt8XzGhERnVuzoxl52jzMKZkz/JpUceNKACJSAnfAzaOSNC7Xz7oeXb4ubLZtljsU1Ro1cRMEoQjAUwD0p166A0CTKIpWADcIgmCM4zUiIjqHJkcTFpQtOK3pvzSvFDlZOay4EZEiMHGj8brEcglKcks4pGQCxlJxCwO4EUD/qb//GIDnTv36fQBL4njtNIIgfFUQhB2CIOzo7u6OP3oiojTRP9SPg66Dpx2TBABBEGA2mFlxIyLZ+UN+DIYGUZTLHjeKn06jw7XV1+L99vfR7ePn/vEYNXETRbFfFMW+mJf0AKRHv70AKuJ47cxr/04UxSWiKC4pKysb3z8BEVEa2Nm1EyJELKk46xkXLEYLh5MQkeyGl2+z4kbjtLZmLcJiGH87/De5Q1Gl8Qwn8QDIO/Vrw6lrjPU1IiIawQ7HDmg1WtSW1p71NbPBjPaBdoiiKENkRERRUuLGqZI0XlMnTcWSiiVY37aef6aNw3iSqSYA9ad+vRDAsTheIyKiETQ7mjG/ZD5ytblnfc1sMMMT9KB/qH+EdxIRpYbL7wIAFOQUyBwJqdnamrU4OXASOxw75A5FdcaTuD0F4MeCIPwSwFwA2+J4jYiIzjAYGsQe557T9rfFshgtADhZkojkNVxxY48bTcDHp34cxmwjXjj4gtyhqM6YEzdRFD926q/HAXwcwGYAV4qiGB7ra4kOnogoHbR2tyIkhs4aTCKxGE4lbgNM3IhIPuxxo0TI1ebi6hlX483jb6Iv0Df6G2jYuPrORFG0i6L4XOzQkrG+RkREp2tyNEGAgAvLLxzx69IuNw4oISI5uf3RxI1HJWmirq+5HkORIbx85GW5Q1EVDgwhIpJZk6MJFxRfAGP2yOsuDdkGFOYUsuJGRLJyBVyYlD0JWo1W7lBI5S4ovgDzSuZhXds6DimJAxM3IiIZBcNB7Oredc5jkhKLgSsBiEhebj+Xb1PirK1ZizZXG/b07JE7FNVg4kZEJKO9vXvhD/tRVz7yYBKJ2Whm4kZEsnIH3CjMZeJGifGp6Z9CnjYP69rWyR2KajBxIyKSUbOjGQDOOVFSYjZEE7dwhHOeiEge7oCbO9woYQzZBnxi6ifw9yN/hy/okzscVWDiRkQkoyZHE6ZNmobSvNLzfp/FaEEoEkL3YHeKIiMiOp0r4OJRSUqoG2bdAF/Ih9eOvSZ3KKrAxI2ISCYRMYLmruZR+9uAjyZLnhw4meywiIhGxB43SrSFZQsxo2AGj0uOERM3IiKZtLnaMDA0MKbEbbJhMgCuBCAieQyGBuEP+9njRgklCALW1qzFru5dOOQ6JHc4isfEjYhIJk2OJgCj97cBgMlggkbQcCUAEclCWpTMHjdKtGtmXgOtRov1h9bLHYriMXEjIpJJc1czTHoTqvRVo36vTqODKd/EihsRycLldwEAK26UcMW5xbh88uXYeHgjhsJDcoejaEzciIhkIIoimhxNWFyxGIIgjOk9XAlARHJxBU4lbuxxoyS4vuZ6uANuvH3ybblDUTQmbkREMjgxcALOQeeo+9timQ1mHpUkIlnwqCQl0/Kq5ajSV2HdQQ4pOR8mbkREMpD2ty2pWDLm91gMFnQPdsMf8icrLCKiEfGoJCWTRtBgTc0abO3YygeU58HEjYhIBjscO1CUU4TpBdPH/B6zMboSwO6xJyssIqIRuQNuCBAwKXuS3KFQmrqu+jpoBA2e2f+M3KEoFhM3IiIZNDuaUVdRN+b+NiBacQOAdg+fRhJRarn8LhizjdBqtHKHQmnKpDfh6hlX45n9z+BE/wm5w1EkJm5ERCnW6e1Eu6d9TPvbYlmMpxI3HiMhohTrC/ShKJf9bZRcd9fdDZ1Gh1/s+IXcoSgSEzciohST+tvGsr8tVkluCXKzcjlZkohSzhVwcaIkJV1Zfhm+uuCrePfku2i0NcodjuIwcSMiSrHmrmbodXpcUHRBXO8TBAFmA1cCEFHquQNuTpSklLhl7i2YbJyMRz54BMFIUO5wFIWJGxFRijU5mrCobNG4ekXMRq4EIKLUc/ldKMgpkDsMygDZWdm4b8l9ONx3GM8deE7ucBSFiRsRUQq5/W4cch+Ku79NYjFYYPPYIIpigiMjIjo39rhRKl02+TIsr1yOJ3Y+MbyKgpi4ERGlVHNXtL9tvImb2WCGJ+gZXoZLRJnlreNv4b93/ndK7zkYGoQ/7GePG6WMIAh4YOkD8AV9eGLnE3KHoxhM3IiIUqjJ0YRsTTbml84f1/ulyZLscyPKPBExgkd3PIrf7PoN3jv5Xsru6/a7AYAVN0qp6qJq3HjBjXj+4PM40HtA7nAUgYkbEVEKNTuaUVtWi+ys7HG932yILuE+6TmZyLCISAWaHE1o97QjNysXP9v+MwyGBlNyX1cgelSNFTdKtW8u+iaM2UY88sEjbBEAEzciopTxBX3Y17sPdeXxrQGINVxxG2DFjSjTrG9bD6POiP+67L9g89jw+5bfp+S+UsWNiRulWkFOAW5fdDu2d27HWyfekjsc2TFxIyJKkZ3dOxEWw1hSsWTc19Dr9CjKKUK7h5MliTLJwNAA3jj+BlZNX4V6cz2umXEN/rjnjzjSdyTp93YHTiVuuUzcKPVumHUDqgur8eiORxEIB+QOR1ZM3IiIUqTJ0YQsIQsLyxdO6Dpmg5kVN6IM84+j/0AgHMDamrUAgHuX3Is8bR5+uvWnST9CJh2V5B43koNWo8WDFz0Im8eGp/Y8JXc4smLiRkSUIk2OJswung29Tj+h61iMFg4nIcowG9o2oKaoBnNL5gIASvNKcdeFd2Fb5zb8/ejfk3pvd8ANAQImZU9K6n2IzmVZ5TJcOeVK/G/r/8LhdcgdjmyYuBERpcBQeAit3a3jXgMQy2www+61IxwJJyAyIlK6g66D2N2zG2uq10AQhOHXb5h1A+aXzMcvPvgFBoYGknZ/l9+FSTmTkKXJSto9iEZz75J7EY6E8VjzY3KHIhsmbkREKbDbuRtDkSHUVYx/MInEYrQgFAmhy9eVgMiISOk2tG2AVqPF1TOuPu31LE0Wvr/i+3AFXPjVh79K2v37An08Jkmym2ycjC/O+yJePvIydnbtlDscWTBxIyJKAWnx9kQmSkqklQAcUEKU/oLhIF4+8jIum3zZiHvU5pXMw40X3IhnDzyLPT17khKDK+DiRElShC/XfhlleWV4ePvDiIgRucNJOSZuREQpsMOxA9WF1QlZYCutBGgfYOJG6rSrexcue+4ydHo75Q5F8d5tfxfugBtrqtec83vuuPAOFOUU4aEtDyXlCLXb7+ZESVKEfF0+7ll8D3b37MbGwxvlDiflmLgRESVZOBLGzq6dCam2AYBJb4JG0LDiRqq1s2snnINOvN/+vtyhKN76tvUozy/HyqqV5/weY7YR9y+9H7t7duOFgy8kPAZW3EhJPj3j01hQtgCPNT8Gb9ArdzgpxcSNiCjJDrgOwBv0JmQwCQDoNDqY8k2cLEmq1eHtAAA02BpkjkTZOr2daLQ34tqZ1446GORT0z+FZaZl+GXzL+EcdCYsBlEU2eNGiqIRNHhw6YNwDjrxu5bfyR1OSjFxIyJKsiZHEwAkZDCJxGK0cJcbqZbdYwcAbO/cjmA4KHM0yrXx8EZExMh5j0lKBEHAd5d/F4PhQfznjv9MWAyDoUEEwgEelSRFqS2rxeqZq/GnvX/Cif4TcoeTMkzciIiSrNnRDLPBDJPelLBrmg1mHpUk1erwdiA3KxfeoBc7uzNzOtxoImIEGw5twFLTUkyeNHlM75lRMAO3zrsVG49sxAedHyQkDnfADYDLt0l57q67GzqNDo/ueFTuUFKGiRsRURKJoogmR1PCjklKLEYLnINODIYGE3pdolSwe+y4cuqV0ApabLZtljscRWpyNOHkwMkxVdtifWXBV2A2mPHQ1ocSUs10BVwAgIKcgglfiyiRyvLL8NUFX8U7J99Bo71R7nBSgokbEVESHe07ClfAlfDETVoJIB05I1ILb9CL/qF+1BTVYGH5Qmy2M3EbyYuHXoRBZ8CVU6+M63152jx856Lv4EjfETy99+kJx9Hn7wOAhEzEJUq0W+begsnGyXhk+yMIRtL/2DUTNyKiJGrqiva3JaPiBoADSkh1pIcNVfoq1Jvrsb93f0KHaaSDgaEBvH7sdayavgp52ry433/p5Etx+eTL8duW30744Y5UceNUSVKi7Kxs3LfkPhzuO4znDjwndzhJx8SNiCiJmhxNKM0rxRTjlIReV6q4nRw4mdDrEiWbNFGy0lA5POI+U445jdWrx16FP+yP+5hkrAcvehAA8PPtP59QLOxxI6W7bPJlWF65HE/sfAIuv0vucJKKiRsRURI1O5pRV14HQRASet2S3BLkafNYcSPVkX7PVumrMLt4Nopzi7kW4Awb2jagurAa80vnj/salYZKfGPhN/DOyXfw7sl3x30dl98FAQKM2cZxX4MomQRBwANLH4Av6MMTO5+QO5ykYuJGRJQkdo8dHd6OhB+TBKJ/UJkNZq4EINXp8HRAp9GhJK8EGkEDa5UVW+xbEI6E5Q5NEdpcbWh1tmJN9ZoJP/D5/NzPo7qwGj/b9jP4gr5xXcMdcKMgp2DUPXJEcqouqsaNF9yI5w8+j4Oug3KHkzRM3IiIkkTa35aMxA3gSgBSJ7vXjkp9JTRC9CPISvNKuANu7OvdJ3NkyvDioReh1Whx9cyrJ3wtnUaH7y//PuxeO37f+vtxXcMdcLO/jVThm4u+CWO2EQ9vfxiiKModTlIwcSMiSpImRxOM2UZUF1Yn5foWowU2jy1t/4Ci9NTh6UCloXL471dWrYQAgcclAQTDQWw8vBGXTb4MxbnFCbnm4orFWD1zNZ7c8ySOuI/E/X63382JkqQKBTkFuH3R7djeuR1vnXhL7nCSgokbEVGSNDmaUFdel7QjRmaDGd6gd3h4AJEa2L12VOmrhv++OLcYc0vmcp8bgPfa34Mr4MJ11dcl9LrfWvIt5Gvz8dC2h+J+0OMKuFhxI9W4YdYNqC6sxqM7HkUgHJA7nIRj4kZElAQ9gz041n8MdRV1SbuHxcCVAKQugXAAzkHnaRU3ALCarWhxtqAv0CdTZMqw4dAGlOeVD0/bTJTi3GLcVXcXPuj8AC8feTmu9/KoJKmJVqPFgxc9CJvHhqf3THyPodIwcSMiSoLmrmYAyetvAwCzMboSoH2AfW6kDp3eTgAfrbOQWKusiIgRbOvYJkdYiuDwOtBga8C11ddCq9Em/Po3zLoBtaW1eHTHo+gf6h/Te0RRhNvvRmEuEzdSj2WVy3DllCvx+9bfw+F1yB1OQjFxIxqDvkBf2p6XpuRocjQhNysXc4vnJu0eUsWNA0pILaRl0JX60ytuC8oWwKgzYrM9c49LbjyyERExkvBjkhKNoMEPlv8A7oAbjzc/Pqb3DIYGMRQZ4g43Up17l9yLcCSMXzb/Uu5QEoqJG9EY/GXfX3D3O3ejZ7BH7lBIJZodzVhYthC6LF3S7pGvy0dxbjErbqQa0vLtKkPVaa9rNVosr1qOBltDRg7bEUURG9o2YEnFEkyZNCVp95lTMgc3z74Zzx14Dnuce0b9flcgusyYRyVJbSYbJ+OL876IjUc2Ylf3LrnDSRgmbkRjIP1HL33oIDqfgaEB7O/dn9RjkhKzwcweN1INu8cOjaBBeX75WV+zVlnR5evCYfdhGSKTV5OjCScGTmBNzZqk3+v2RbejNK8UP9n6k1F357n90cFHTNxIjb5c+2WU5ZXh59t+jogYkTuchGDiRjSKiBhBq7MVABM3GpudXTshQkzqYBKJxWBh4kaq0eHtQHl+OXSasyvRVrMVADLyuOSGQxug1+lx5ZQrk34vQ7YB9y+9H3t79uL5g8+f93ulibVcB0BqlK/Lxz2L78Hunt3YeHij3OEkBBM3olEc7z+OgaEBAB811hOdT5OjCVpBiwVlC5J+L7PRjA5Px6hPzomUwO45fRVALJPehJkFMzNun5tnyIM3jr+BVdNXIV+Xn5J7fnLaJ7G8cjkeb34czkHnOb+PRyVJ7T4949NYULYAjzU/Bm/QK3c4E8bEjWgUUrUNYMWNxqbJ0YS5pXORp81L+r0sBgtCYggOX3pNzqL01OHtOGsVQCyr2YomRxN8QV8Ko5LXq8dexWBoEGuqk39MUiIIAr637Hvwh/14dMej5/w+6agkK26kVhpBgweXPgjnoBO/b/m93OFMGBM3olG0dLdAr9NjinEKK240Kn/Ij909u1PS3wZwJQCpRygSQqe385wVNyCauAUjQexw7EhhZPLacGgDZhbMRG1pbUrvO61gGm6bfxteOfIKtndsH/F7XAEXNIIGxmxjSmMjSqTaslqsnrkaT+99Gif6T8gdzoQwcSMaRauzFfNL5qPKUMXEjUbV6mxFKBLCkoolKbmftA+LfW6kdN2+boTF8HkrbosrFiM3KxebbZnR53bYfRgt3S1YU7MGgiCk/P5frv0yLAYLHtr2EILh4Flf7wv0oSC7ABqBHxdJ3e6uuxs6je68FWY14H+JROfhD/lxsPcgastqYdKbmLjRqJocTRAgYFH5opTcz6Q3IUvIwsmBkym5H9F42b3RHW7nq7jlZOVgiWlJxgwo2dC2AVpBi6tnXC3L/XO1ufjusu/iaN9RPLX3qbO+7vK7uHyb0kJZfhm+suAreOfkO2i0N8odzrgxcSM6j329+xASQ6gtrUWlvhLOQeeITyWJJE2OJswqmoVJ2ZNScj+dRgeT3sSKGyne8PLt81TcAKDeXI/j/cfT/mFEMBLExiMbcenkS1GSVyJbHBdbLsaVU67Eb3f99qwj1+6Am8u3KW18Ye4XMNk4GY9sfwShSEjucMaFiRvRebR0twAAFpQtgElvggiRQyDonIKRIHZ170rJGoBYXAlAaiANd6rUnz9xs1ZF1wI02tT7VHws3j/5Pnr9vVhbs1buUPDARQ9AEAQ8vP3h0153BVwoyCmQKSqixMrOysZ9S+7D4b7DeO7Ac3KHMy5M3IjOo9XZiip9FUrzSmHSmwBwsiSd2/6e/RgMDaZsMInEbDRzOAkpnt1jR3Fu8ajTVqdOmgqzwYwGe3qvBdhwaAPK8sqwsmql3KHApDfhmwu/iXfb38XbJ94efr3P38eJkpRWLpt8GZZXLscTO58YnpqqJkzciM6jtbsVtWXRSV9S4sY+NzqXJkcTAKQ8cbMYLOjx92AwNJjS+xLFo8Pbcd7+NokgCLBWWbG9Y3vaHk3v8nVhk20Trq2+FlqNVu5wAACfm/s5VBdW4+fbfw5f0AdRFOEKuLjDjdKKIAj49tJvwxv04tc7fy13OHFj4kZ0Ds5BJ+xe+/CIZlM+Ezc6v6auJkydNBWleaUpve/wZMkBHpck5bJ77KP2t0msZit8IR92du9MclTyeOnwS4iIEVxXfZ3coQzTaXT4wfIfoMPbgd+2/Ba+kA/BSJA9bpR2aopqcOMFN8If8kMURbnDiQsTN6JzaO2OLt5eULYAAJCvy0dBTgETNxpRRIyg2dGc8mobAFiMFgBcCUDKJYriqDvcYi2rXAatoEWDLf2OS4qiiBcPvYi68jpMnTRV7nBOU1dRh+uqr8PTe54ePkHAHjdKRw9c9AAeqn9IljUcE8HEjegcWp2t0ApazCmeM/xapb6SPW40okPuQ+gf6kddeWoHkwAfVdzaPexzI2Xq9ffCH/aPueKm1+mxqHxRWu5za+5qxvH+44oYSjKSexffC322Hj/e8mMAYI8bpSW17iZUZ9REKdDibEFNUQ1ytbnDr5nyTej0seJGZ2t2NANIfX8bgOGBDxxQQkolPfAaa8UNiB6XPOA6gG5fd7LCksWGtg3I1+bj41M/LncoIyrKLcLddXejy9cFAOxxI1IQJm5EIwhHwtjt3D18TFJi0pvQ6WHiRmdrcjShIr9iuPqVSoIgwGww86gkKZa0w63KMPbErd5cDwCqXpZ7Jm/Qi9ePv45V01chX5cvdzjntLZm7fCff0zciJSDiRvRCI72HYU36B0eTCIx6U0YCA7AM+SRKTJSIlEU0exoRl1FnWzn5S0GC49KkmIN73Ab41FJAJhVNAsluSVpdVzy1aOvYjA0iDU1a+QO5bw0ggb/bv334YXFRGkn4AFUNpgEYOJGNKJW5+mDSSTS4th0GFCyo3MHTvSfkDuMtNA+0I6uwS4sqVgiWwwWowW2AZvqJmRRZrB77DDoDJiUPWnM79EIGljNVmzp2IJwJJzE6FJnw6ENmFEwAwtKF4z+zTKbVjAN9y+9H1maLLlDIUq8l+4AnrpGdcmbMpaHEClMi7MFxmzjWRO/hne5+TpRXVQtR2gJEYqE8LU3voYsTRa+c9F3cF31daqbrKQkOxw7AECWwSQSs8EMX8gHV8CF4txi2eIgGkk8qwBiWauseOnwS9jbs3d4p6ZaHXEfwa7uXfjW4m/x5y3JLxwEgoOn/ucb4den/ho69booAktuBbL1ckc+ca5jwN4XgZV3ACr7b5GJG9EIWrtbUVtae9bUIanipvbJkl2+LgxFhlCcXYwfNv4QjfZG/HDFD2HMNsodmio1dzWjMKcQMwpnyBbD8EqAARsTN1Icu9ce12ASyYqqFRAgoMHeoPrEbcOhDdAKWlw982q5Q6F04XUCH/4peuwv5D876RopEZN+HQnFf7+gD7j024n/50i1rb8BBA2w7OtyRxI3Jm5EZ/AFfWhzt+Fjkz921tfK8sugETSqPyopDbH4af1Psa93H3794a/R6mzFzy/+ORaVL5I5OvVpcjShrrxO1vHCsSsB1P4Bl9JPh6djXBXpotwizCuZh822zfjGwm8kIbLUCEaCeOnwS7jEcglK80rlDofSxdbfAJsejSYhunxAl3fqf/kf/TWvCDBWnv7aaX+Vfp17nq/lAS/8M7Dtf4AVtwPZyh2sMypfL9D8J6D2M8Ck+B8myY2JG9EZ9vbsRUSMnNXfBgBajRZleWVpk7hNNk6G1WzFUtNSPPD+A/jSq1/Cvyz6F9w2/zb2NYxRl68LJwdO4sYLbpQ1Dilx42RJUpqBoQEMBAfimigZy2q24vetv0dfoE+1y6A3tW9CmSl+fQAAIABJREFUr79X8UNJSGWONQDmxcCX30r+kb/6e4AnPwXs/Atw0VeSe69kavojEPRGE1AV4nASojNIg0nml84f8esmvUn1iZvdY4cAYbhnb2HZQjx/zfP4+NSP4/EPH8dX3/gqHF6HzFGqg7S/Tc7BJACQr8tHcW4xd7mR4kirAMbT4wZE1wJExAi2dmxNZFgptaFtA0rzSodXHBBN2JAXsDUB0y5OTZ/W1JWAZSnQ+DgQHscxSyUIBYBtvwVmXg6YRv6Mp3RM3IjO0NLdAovBcs4+oUp9pep73GweG8ryy5CdlT38mjHbiEcueQQ/WfkTtDpbccPGG/DuyXflC1Ildjh2IF+bjwuKL5A7FK4EIEWSfl6a9ePbcTi/dD6M2UbVrgXo9nVjk20TVs9cDa2GB50oQU5uByLBaOKWCoIQrbq5TwB7NqTmnonW8hzgcQAr75Q7knFj4kZ0hhZny3l7hEx6ExxeByJiJIVRJZbdYx9xUbQgCFhTswbPXv0sTHoT7nj7Dvxs288QCAdkiFIdmruasah8kSI+kJmNZtgGeFSSlGWiFTetRovllcux2bZZlesuNh7ZiLAYxppqHpOkBDrWAAhZwJRlqbvnrFVA6QXA5l+qbow+IhGg8VdARS0w42NyRzNuTNyIYji8DnT5urCwbOE5v8ekN2EoMoRef28KI0ssu8d+3n6T6QXT8ZdP/QWfn/N5/HX/X/HZVz6LI+4jKYxQHfoCfWhztWFxxWK5QwEQrbh1eDsQGs+0MKIk6fB2ICcrByW5JeO+Rr25Hl2DXTjkPpTAyJJPFEVsaNuAuvI6TCuYJnc4lE6ONQBVi4CcFE6D1mgA652AoxU49Fbq7psIh94EnAdUuQIgFhM3ohhSf1tt6fkrbgBU2wMWioTg8DlGrLjFys7KxgMXPYBfX/5rdPu6cdMrN2F923pVPvFOlg+7PgQg7/62WBajBWExDIdPnb83KT3ZPXZU6isntLtsZdVKAFDdccmd3TtxrP8Yrqu+Tu5QKJ0M97fJ0DNZ+0+AsQrY/Fjq7z0RjY9H456/Vu5IJoSJG1GMFmcLdBodZhfPPuf3SLvc1DqgpNPbibAYHjVxk1w6+VK8sPoFLChbgH9t/Ffc99596B/qT3KU6tDkaIJOo1PM+P3hlQAcUEIK0uHtGP65OV4mvQnVhdVosDckKKrUWN+2HvnafFw17Sq5Q6F0kur+tljabGDFvwDHNgHtO1J///GwfxiNd/k3gCyd3NFMCBM3ohit3a2YXTz7tKEdZ5IqbmodUCL1m8Qzmrs8vxy/+/jvcFfdXXjrxFv4zEufwc6unckKUTWaHE2oLa1FTlaO3KEA4EoAUqbRjmaPlbXKimZHM3xBXwKiSj5v0IvXjr2GT07/JPJ1Kt57RcpzfHO0v21yCvvbYi3+IpBbADT8lzz3j1fjr4GcScDiL8kdyYQxcSM6JRwJY0/PnvMekwSAopwi5GTlqLbiJn2oj3fCm0bQ4Mu1X8ZTq56CIAj40qtfwu9afodwJJyMMBXPF/RhX88+xfS3AdGHCllCFitupBiBcAA9/p4JV9yA6D63YCSIHQ51POV//djrGAwNcigJJZ7U35Y7SZ775xiBpV8B9r8CONvkiWGspCmYi78o37+vBGLiRnTKIfchDIYGRz32JgjR/Weqrbh5T9/hFi9p59snpn0Cv/rwV/jKG19RbRI7Ebu6dyEkhhSVuGk1Wpj0Jq4EIMXo8ER/Tiai4lZXUYc8bR4abOo4Lrm+bT2mF0w/77ArorgN+aJHFOXob4u17OuANic6YVLJtv4mOoxk2dfljiQhmLgRndLibAEALChdMOr3mvQmdPrUmazYPXZU6Cugm8A5b2O2EQ9f/DD+zfpv2O3cjRs23oC3T7ydwCiVr7mrGRpBo7gPZRajhUclSTGGVwEkoOKWk5WDpaalqhhQcqTvCHZ278Sa6jUTGspCdJZ2GfvbYhnKgEWfA1qeBfoV+iB70AU0PQXMvx4osMgdTUIwcSM6pbW7FYU5hZhsnDzq95ryTej0qDNxax9oR5V+4k+/BUHAddXX4dmrn0WVvgp3vXMXfrrtpxmz863J0YTZxbNhyDbIHcppLAYLj0qSYti98ffUns/KqpU4MXACJ/tPJuR6yfLioReRJWThmpnXyB0KpRtpf5tc/W2xVt4BRELA1v+WO5KRNT0JBL3AitvljiRhmLgRndLqbEVtae2Yno5WGirRPdiNYCSYgsgSy+4defn2eE0vmI4/f+rPuGXuLXhm/zO4+ZWbcdh9OGHXV6Kh8BBaulsUdUxSYjFa0OvvVc0AB0pvdo8dWUIWyvPLE3K9enP0eNhmu3KrbsFIEC8degmXWC5BaV6p3OFQupG7vy1W8XRg3hpgxx+BQbfc0ZwuNARs/Z/osu3K0U9SqQUTNyIAniEPDrsPj3msuynfBBEiunxdSY4ssYLhILp8XQl7+i3JzsrGt5d+G09c8QR6Bntw08s34fmDz6ftzre9PXsRCAewuFx5iRsnS5KSdHg7UJ5fDq1Gm5DrTTFOgcVgUfRxyYb2BvT4eziUhBJPKf1tsax3AUMDwI7/kzuS0+1+AfB0AivvlDuShGLiRgRgT88eiBDH1N8GqHeXW6evExExktCKW6xLLJfghWtewKLyRfjJlp/gW+99C32BvqTcS07SVLsLKy6UOZKzMXEjJZGWbyeKIAiwmq3Y1rkNwbAyTzxsOLQBJbklqLco6MM1pQel9LfFqlwIzLw8Wt0K+uWOJkoUgcZfAeXzorGlESZuRIgekwSA+aXzx/T9at3lJg0KSFbiBgBl+WX47cd/i3sW34N3TryDz2z8DFq7W5N2Pzk0O5oxo2AGinOL5Q7lLBZjtAGbfW6kBB3ejoT/vLFWWTEYGsSHXR8m9LqJ4Bx04v3297G6ejV0GnUv+iUFUlJ/Wyzr3YC3C9j1V7kjiTr0FtC1N9qDl2bDgZi4EQFo6W7BtEnTUJBTMKbvlxI3tVXcxrN8ezw0gga3zb8NT696GgDwvc3fS+r9UikcCePDrg8V2d8GRPcM5mnzWHEj2YUiIXT5ulBpSFzFDQAuqrwIWo0WDXblrQXYeHgjwmIY11VfJ3colI6U1N8Wa/olQFUdsPlxQAm7XRsfB4yV0WmSaYaJG2U8URSHB5OMVb4uH5OyJ6kucWv3tEMjaFChr0jJ/WrLanHL3FtwtO9o2lSADroOwhP0KDZxEwQBFqOFu9xIdl2+LoTFcEKm2MbS6/SoK69TXJ+bKIpY37YeF5ZfiBkFM+QOh9KNEvvbJIIA1N8NuI4Ce/8mbywdu4Cj753aM5ctbyxJwMSNMl6ntxPOQeeYB5NIKvWVqkvc7B47KvIrUnqEx2q2AgAa7Y0pu2cySdPsLjJdJHMk52Y2mNMmUSb1Gt7hluCKGxD9uXLQdVBRA6J2de/Csf5jHEpCyaHE/rZYs68GimcCmx+L9pjJpfHXQLYRWHKrfDEkERM3yni7nLsAjG3xdiyT3qTKHrdkH5M80/RJ02E2mNFgU96xpvHY1L4Jc4rnoCy/TO5QzsliiC7hTtepnqQO0s/HRFfcgGifG6CsB0Lr29YjT5uHT0z7hNyhUDo61gAIGuX1t0k0WYD1zmjF68i78sTgPgnsXgcs/iKQO7bWF7Vh4kYZr7W7FTlZOZhVNCuu95n0JtVV3GweW1IHk4xEEARYq6zY1qHcKXBj1T/Uj13du4Z3SSmVxWjBYGgQvf5euUOhDJbMitusolkozStVzHHJXd27sPHwRlw942rodXq5w6F0dKwBqFRgf1usBTcBhopo1U0O2/4n+tdlX5fn/inAxI0yXquzFXOK50CXFd/xQZPehP6hftUsOpZ2uKU6cQOix5p8IZ8ip8DFY6t9K8JiGBdbFHpU5RSuBCAl6PB2oCS3BDlZOQm/tvRAqNHeiLDMwxD6An24/737UaGvwN2L75Y1FkpTQz7A1qTM/rZYulxg+TejFTd7iv+8H3QDTU8C89cChZNTe+8UYuJGGS0YCWJvz964+9sA9e1y6/B2QISY8qOSALCschm0gjKnwMVjk20TjNnGuAbZyMFi4EoAkl+yj2ZbzVb0D/VjT8+epN1jNKIo4vsN30f3YDf+49L/wKRsBVdDSL3aPwDCQ8rtb4u15FYgZxKw+ZepvW/zU8CQB1hxe2rvm2JM3CijtbnaEAgH4u5vA9S3y02qvshRcdPr9Liw4kLFHGsaD1EU0WBrwMqqldBqtHKHc17Sh2VW3EhOdm9il2+faUXlCggQZP258vTep/Fu+7u4b8l9mFc6T7Y4KM1J/W1TlssdyehyC4Alt0WnS/YcTs09Q0PRBeDTL4muS0hjTNwoo0mLoTOh4paqHW7nUm+uV9wUuHjs790P56ATF5uV/8QzX5ePktwSJm4km4gYQYenI6k/bwpzC1FbWitbJb+luwWPNT2GK6Zcgc/O/qwsMVCGUEN/W6zl3wA0WqDxV6m53571wIAdWHlXau4nIyZulNFanC0ozi0e19SzsvwyCBBUVXHLErJQkZ+aHW5nkqbAqbXqJk3FlNYbKJ3ZyJUAJJ9efy+GIkNJrbgB0f8edzt3oy/Ql9T7nCm2r+3HK38MQRBSen/KIEM+wKbQ/W3nYjQBC28Gdv4VGHAk916iGF38XT4XqL4iufdSACZulNFana1YULpgXH/o6jQ6lOWXqafi5rXDpDfJdsxvVtEslOWVqXYtQIOtAXNL5qI0r1TuUMbEYuASbpJPqir8K6tWIiJGsKVjS1LvE0sURfxg8w/QNdiFX1zyCxTkpOfYcVIINfW3xbLeFY1bmvSYLIffBrr2RHvbMuABChM3ylh9gT4c7Ts6rmOSEjWtBJBjh1ssQRBgNVuxpWMLQpGQbHGMR1+gDzu7dyp+DUAss8GMTm+n6v5dU3qwe0+tAkhyxW1+6XxMyp6U0kr+n/f9Ge+cfAf3Lr53Qn9+EI2JmvrbYpXMBOauBj74P8Dfn7z7NP4KMJiA2huSdw8FYeJGGWuPMzqJbEFZ/INJJJX6SnT61JG42QZsSVmEG496cz0Ghgaw27lb1jjitaVjCyJiRBX9bRKL0YKwGFbNgwVKLx2eU8u3k/ywSKvRYkXVCjTaGlOycL61uxX/2fSfuGzyZfj8nM8n/X5Equtvi2W9Gwj0Rcf0J0NnK3DkHWDZ1wBt4teOKBETN8pYLc4WCBAwv2T+uK9hyo9W3FLxgWEihsJD6BqUZ4dbrOWVy6ERNKo7LtnQ3oCCnALFrwGINbwSgMclSQZ2jx3GbCOM2cak38taZUXXYBfa3G1JvU9foA/3v38/yvPK8W/Wf2NfGyWfGvvbYpnropMetzwBhAKJv37jr4FsQ3SKZYZg4kYZq9XZihkFM2DINoz7GpWGSgTCAbgCrgRGlnjSABU5j0oCQEFOARaULlBV4hYRI9E1AJUrkaXJkjucMTMbTy3hHuBkSUq9Dm9Hyir8K6tWAkju4CNRFPHDzT+Ew+vALy5lXxuliFr722JZ7wY8nUDLs4m9bl87sPsFoO4LQF5hYq+tYEzcKCOJoojW7tYJ9yeY8tWxy00aCy934gZEp8Dt6dmDnsEeuUMZk/29+9Hj70G9RV1PPCvyK6AVtKy4kSzsXjsqDcntb5NU6CtQU1ST1MTtL/v+grdPvo17Ft8zoeP1RHFRa39brJmXA6YF0cmPkUjirrvtf6ITJZd9PXHXVAEmbpSR2j3tcAVcEz76ZjJEEzel9xFJE96k43NykgZ8pHIK3EQMrwGoUscaAIlWo4VJb2LFjWTR4UldxQ0A6qvq0dzVDF/Ql/Br73buxn80/Qc+NvljuGXuLQm/PtE5qbm/TSIIQP3dQE8bcOCVxFzT3wfseBKYdx1QNDUx11QJJm6UkaTF2xN9cipV3JSeuNk8NmgFLcryy+QOBXNL5qIop0g1+9w2tW/CvJJ5KMkrkTuUuFmMFi7hppTrH+qHJ+hJaYXfarYiGAnig84PEnrd/qF+3PfefSjLK8ND1ofY10apo/b+tlhzrgWKpgEN/xWtkk1U89PA0EB0BUCGYeJGGanV2Yo8bR6qC6sndJ3i3GJka7JVkbhV6Ctk2+EWSyNosNK8Eo32RkTEBB6bSIK+QB9anC242KLO/gKzwcyjkpRy0kTJZK8CiHVh+YXI0+YltH9WFEX86+Z/ZV8byWO4vy0NErcsLbDyDsDWFK0iTkQ4CGz9TbTvz1yXmPhUhIkbZaSW7hbMKZ4z4URGEASY9CbF97jZPXbZJ0rGslZZ0evvxb6efXKHcl5Scqmm/W2xLEYLev29STk+RnQuqVq+HSs7KxsXmS7CZnviKvl/3f9XvHniTdy9+G4sLFuYsOsSjcnxzervb4u16HOAvgzY/NjErrNnA9BvA1bemZi4VIaJG2WcofAQ9vXuS9gfxJX6SsVX3ORevn0maQqc0qdLNtgaUJhTOKGVEXLiSgCSQ6qWb5/Jarbi5MBJnOg/MeFr7XHuwaM7HsXHLB/DF+Z+IQHREcXpWANQuRDITZNKry4vOkjk0JvR/WvjIYrRISdls4HqKxMbn0owcaOMc6D3AIKR4IQnSkoq9BWKrrgFwgF0D3YrquJWkleCuSVzE/p0PNGG1wBUqWsNQCzp/3MOKKFUsnvsyM3KRXFucUrvW18VrYxP9OdK/1A/vvXet1CaV4qH6tnXRjIIDkaPSqbDMclYS/85undt8y/H9/4j7wKO1mhvmyYzU5jM/KemjNbibAGAhC1TrtRXwjnoRDASTMj1Ek3qN1FS4gZEp0vu6t6FvkCf3KGMaF/PPvT6e1V7TBKIHpUEWHGj1OrwdsCkN6U84Zk8aTImGydPaPCRKIr4UeOPon1tl7CvjWSSDvvbRpJXBCz+ErB7PeA6Hv/7G38F6MuBBf+U8NDUgokbZZxWZyvK88ph0psScj2T3oSIGEG3rzsh10s0Je1wi1VvrkdEjGBbxza5QxnRJtsmCBBgNatrDUCswpxC5GvzOVmSUkrOo9nWKiu2d27HUHhoXO9/Zv8zeOP4G7ir7i4sKl+U4OiIxigd9redy4p/if6zbfl1fO/r3A0cfgtY9jVAm5Oc2FSAiRtlnEQs3o4l9XEotc9N+tCutIpbbWktjDqjYvvcGmwNmF86P+XHvRJJEIToSgAelaQU6vB2pLy/TVJvrsdgaBAfdn0Y93v39ET72i6xXIIvzGNfG8ko3frbYk2qAhbeCDT/CfA6x/6+LU8AOj2w5LbkxaYCTNwoo7j9bpwYOJGwY5IAhit3Su1zs3vs0R1uefLvcIul1WixvGo5Nts2Q0zEXpcEcvvdaOluUfUxSQlXAlAqDYYG0evvle1B0VLTUug0uriPSw4MDeC+d+9DcW4x/t3679AI/HhEMknX/rZYK+8CQn5g22/H9v39dqD1eaDuFiBfvQ9TE4E/mSijtDoTs3g7lpS4KbXiZvfYYdKbFDlgo95cj67BLrS52+QO5TSN9kaIENMmcbN5bIpLjik9SQ+wKg3yVNzydfmoK69Dg33slXypr63D24FHL30UhbmFSYyQaBTp2t8Wq2wWMPvTwPbfAQHP6N+/7X8AMQws/0byY1M4Jm6UUVqcLdAIGswrmZewa+p1ehizjYqtuNm8NpiNyjomKbFWRfvHJjJMIBk22TahKKcoob9P5GIxWjAYGkSPv0fuUCgDSMOQqvTy9dRazVa0udrQ5esa0/c/e+BZvH78ddxZdyf72kh+6dzfFst6N+B3A81Pn//7/P3Ajj8Cc68FiqalJDQlY+JGGaW1uxXVhdXI1+Un9LqV+ko4vI6EXjNRlLZ8O1aFvgI1RTWKStwiYgSN9kasNKt3DUAsaZcbB5RQKkg73OQchiQNFBrLz5W9PXvxyAeP4GLzxfjSvC8lOTKiMUjn/rZYk5cCU63R3rXQeYYJffgnINAPrLwjdbEpGBM3yhiiKKLV2ZrQ/jaJSW9SZMXNH/LDOeiU9en3aOqr6tHU1QRv0Ct3KACiH+R6/b242Jwex1SGVwIMsM+Nkq/D0yF7T21NYQ3K88pH3efmGfLgvvfuQ1FuEf69nn1tpACZ0N8Wq/4eoL8d2P3CyF8PB4Gtv4kmeObFqY1NofhTijLG8f7j6B/qT2h/m6RSX4lOn/J63JTw9Hs0VrMVoUgI2zu2yx0KAGBTe3QNwMqqlXKHkhDS//esuFEq2L12VOgrZK1WC4KAleaV2GLfgnAkPOL3iKKIH235EeweO35xyS9QlFuU4iiJRpAJ/W2xqq8EKuZHF3JHImd/fe/fgL6TwMo7Ux+bQjFxo4whDSZJVsWtL9AHX9CX8GtPhN0TTdyUelQSAOrK65CnzRv16XiqNNgaUFtamzYf5PK0eSjNK2XiRinR4ZFvFUAsq9mK/qF+7O7ZPeLXnzvwHF479hruuPAO1FXUpTg6onPIlP42iSAA1ruA7v1A22unf00Uowld6Syg5hPyxKdATNwoY7R0tyBfm48ZBTMSfu3hyZIKq7qpIXHTZemwrHIZGmwNsk8+dPldaHW2ot6SXsdUzAYzj0pSSti98i3fjrWicgU0gmbEPrd9PfvwyAePoN5cj1vn3ypDdETnkCn9bbHmrQUKpgANj53++tH3gc4WYMXtgIbpioT/JihjtDpbMb90flKO8JjyTyVuHmUlbjaPDVqNFmX5ytrhdqb6qnrYPDYc7z8uaxyb7ZshQkyb/jaJtBKAKJmCkSC6fF2KqLgV5BRgfun8sxI3qa+tMLeQfW2kLEE/0L4jc/rbJFlaYOXtwMmtwImtH73e+CtAXwYsuFG+2BSIP7EoI/hDfhzoPZCUY5LARzuLlFZxs3lsqNJXKf7DyUpztJ+swTb23UvJ0GBrQHFuMeaWzJU1jkSzGC3o8HYgGAnKHQqlMYfXgYgYUUTFDYg+ENrdsxtuvxtAtK/tx1t+DJvHhkcueQTFuZm9yJcUpv0DIBwApmZY4gYAF94C5Jd8VHVz7AUOvQFc9DVAlytvbAqj7E9zRAmyv3c/QmIItWXJSdzK88shQFDcZEm7RxnHlkYz2TgZ0yZNi2tpbqKFI2Fstm2Gtcqq+EQ3XhaDBRExotgl8ZQehpdvK6DiBkT73CJiBFs7ok/xnz/4PF499ipuv/B2LK7ghDpSmEzrb4uVnR9N0g7+I5q0bXkC0OUDS/9Z7sgUJ70+nRCdQ0t3CwBgQWniJ0oCgE6jQ1lemeI+GNs8NkX3t8WqN9djR+cO+EN+We6/p2cP3AE36s3p97STKwEoFaSeWqU8LJpXMg8FOQVosDVgf+9+PLz9YVirrLht/m1yh0Z0tmMNgGkBkFcodyTyuOgr0WTtjR8ALc8CF34eyGdV/ExM3CgjtDpbUamvTGqvl9J2uQ2GBtHr71VN4mY1WxEIB9DkaJLl/g22BmgETdqsAYgl/R5gnxslk7R+RBrWJLcsTRZWVK5Ag60h2teWU4ifXvzTtKuoUxoI+jNrf9tI8ouBui8Ch94ExDCw/BtyR6RI/OlFGSFZi7djVegr4PA6knqPeHR4okmkUp5+j2ZJxRLkZOXI1ue2qX0TaktrUZibfk87K/IroBW0rLhRUnV4OlCWV4acrBy5QxlmNVvR4+/ByYGTePiSh9nXRsok9bdlyv62c1nxL4BGC8y5BihO/ATwdMDEjdJez2APbB5bUhZvx6rUV6LD2yH7SHuJVF1RS8UtV5uLJRVLZEncev292NOzJy2PSQLRykOloZIVN0oqu9c+PKhJKerN9cjT5uHOC+/EEtMSucMhGlkm97fFKpwM3PYa8On/kjsSxWLiRmkvmYu3Y5n0JgTCAbgD7qTeZ6ykD+lqqbgB0afjx/qPpbwytNl2ag2AJX2fdnIlQHIc7TuKUCQkdxiK0OHpQJVeWT9vSvNK8f6N7+OfaznkgBQs0/vbYlmWAPoSuaNQLCZulPZauluQJWRhTsmcpN5HmqSmlD43u8cOnUaH0rxSuUMZM6ni1WhvTOl9N9k2oTi3GHOKk/t7RE4Wo4VHJRPIF/ThR40/wuoXV+PJPU/KHY7sImIEHd4OxVXcgGg1n0ix2N9GcWDidh57evbg5SMvyx0GTVCrsxWzimYhT5uX1PtIDflKmSxp89hQZVD+DrdY0yZNg9lgTulxyXAkjEZ7I+rN9ar6dxUvs8EMV8AFb9Ardyiq19Ldgs9s/AzWt61HYU4hXj/2utwhya5nsAfBSFBxFTcixWN/G8UhfT+lJMCf9/4ZD219iB90VCwiRrDbuTvpxySBjxI3JVXc1NLfJhEEAdYqK7Z1bEMwnJpl0bt7dqMv0IeLzen9hyZXAkxcKBLCb3b9Bl/4xxcQjATxh6v+gFvn34p9vfuGhwFlKmmipJqOZhMpAvvbKA5M3M7j5tk3wxv0YuPhjXKHQuN0tO8oPEFP0geTAEBxbjF0Gp1iJkvavepYvn0mq9kKX8iHD7s+TMn9NrVvgkbQYEXVipTcTy4WQzRxY5/b+JzsP4kvvfol/PfO/8aq6auwbvU6LDEtwRVTrgAAvH3ybZkjlJeUuCpl+TaRarC/jeLAxO08aktrMa9kHp7Z/4xiJgVSfKTF27Vlya+4aQQNTHqTIo5K+oI+Ve1wi7Wschm0Gi0a7Kk5Ltlga8DCsoUoyClIyf3kIiVurLjFRxRFbGjbgBs23oAj7iN45JJH8LOLfwZjthEAMHXSVMwsmIm3T2R24saKG9E4sL+N4sTE7TwEQcBNs2/Ckb4j+KDzA7nDoXFodbbCqDNi2qRpKbmfUpZw2z2nPkSpsN9Er9OjrrwOm22bk34v56AzrdcAxCrIKYBep2fFLQ5uvxv3vnsvftj4Q8wrnYd1q9dh1fRVZ33f5VMuR5OjCW6/MibKysHusWNS9iTodXq5QyFSD/a3UZyYuI3ik9M+icKcQjyz/xm5Q6FxaHW2Yn7p/JQNnajUV6LTJ3/FTe1Pv61mKw5h5Mg7AAAgAElEQVS6DqLL15XU+0jTKzMhcRMEgSsB4tBob8Tal9bi3fZ3ce/ie/G/n/jfc05MvGLKFQiLYbzX/l6Ko1QOu0edR7OJZHV8M/vbKC5M3EaRq83F2pq1ePvk24o4AkdjNxgaRJurLSXHJCUV+RXo8nXJvtdJ+nAuDaRQG2uVFQCSXnVraG9AaV4pZhfPTup9lMJi4EqA0QTCATy8/WF87Y2vwZhtxDOffga3zr/1vA9/5pbMRXl+eUYfl+zwdrC/jShe7G+jODFxG4N/uuCfIIoinjvwnNyhUBz29uxFWAxjQWnyB5NIKg2ViIgROAedKbvnSOweO3KyclCSq84llrOKZqE8rzypawFCkRA22zfDWmVN6zUAsczGaMWNPbsjO9B7ADe9fBP+vO/P+Ozsz+LZq58dU1IvCAIun3w5Gu2NGAwNpiBSZRFFkRU3ongF/cDJ7exvo7hkxqeVCTIbzLh08qVY17YOQ+EhucOhMWrtbgWQmsEkElO+MlYC2Dw2VOorIQiCrHGMlyAIsJqt2NKxJWnVy93O3egf6ke9JXP+0LQYLPCH/ejx98gdiqJExAie2vMUbn7lZrgDbvzmyt/gO8u+E9fi5iumXgF/2J/y5fFK0D/UD1/Ix4obUTxsO071t2XOn0E0cXEnboIgFAmC8HdBEHYIgvDbU6/9nyAIWwRB+H7M9531mprdPPtm9Pp78dqx1+QOhcaoxdkCi8GC4tzilN1T+uAi97Fam8emyomSsaxmKwaGBrDbuTsp199k24QsIQsrKtN7DUAs7nI7W6e3E199/at4dMejuNh8MdatXjeunsfFFYthzDZm5HFJaRiS2n/mEKXUsQYAAjAlc/4MookbT8XtFgB/EUVxCQCjIAjfBpAliuIKADMEQagRBGHtma8lMGZZLK9cjmmTpuH/Hfh/codCY9TS3ZLSahugnCXc6XBsaXnlcmgETdKOS25q35QRawBiDa8E8DBxA4BXj72KtS+tRYuzBT9e+WM8dtlj437Qo9PocKnlUrzX/p7sPa6pJg1DOtfwFiIawbEGoJL9bRSf8SRuPQDmC4JQCGAygOkApOav1wHUA/jYCK+dRRCEr56q3O3o7u4eRyipoxE0uGn2TWjpbsEe5x65w6FRdPm64PA5UtrfBgCGbAOMOqOsFTdv0At3wK36xK0gpwALShckZUCJc9CJfb37MmKaZCzp94RtILMnS3qGPPjupu/i/vfux/RJ0/HCNS9gbc3aCR8tvmLKFegL9KHZ0ZygSNVBWr6txvUjRLIY7m/jGgCKz3gStwYAUwHcCWAfgGwA0qeAXgAVAPQjvHYWURR/J4riElEUl5SVlY0jlNRaPXM18rR5XA2gAnL0t0kq9BWyVtykY0tSdUXNrGYr9vTsQa+/N6HXlap4F1sy6w/NXG0uyvLKMnolQLOjGTdsvAGvHH0F31j4DTy56klMmTQlIddeWbUSOVk5ePtkZh2XtHvtyNPmoTCHlQOiMWF/G43TeBK3fwXwdVEUfwJgP4DPAsg79TXDqWt6RnhN9YzZRlwz4xr84+g/MnrRqhq0OFug1WhlGfNeqa+Ew+tI+X0lw8u3VV5xA4CLzRdDhJjwgQ8NtgaU5ZXhgqILEnpdNTAbzBl5VDIYCeLx5sdx62u3QoCApz75FL656JvQaXQJu0e+Lh8rKlfg7RNvZ9Tkzg5Ph6qHIRGlHPvbaJzGk1AVAagVBCELwDIAP8dHRyEXAjgGoGmE19LCTbNvwlBkCP+fvTMPb/I88/Ut2fImL9h4kTd2GwgYG0iAgNmckJCVhAABMnOm02nndEmaJnN62qTTJE1CliZtTzpb23TmmplOA4Ql+x4giYHYhMULq21WI8kbBmNZXiRL54/XMga8SLI+fZL83tfFFbA/ve/j2P70Pe/zPL/f9prtaociGYTKpkqmJE4hMizS73sb9AZVK26uh/JQSNymjp5KYmSiT9sl7Q47e017KcwsHJEPmplxmSOuVfJ0y2n++sO/5vXK11kxcQVb791KQWqBInsVjSnC3GbmWPMxRdYPRExtJjnfJpF4gpxvk3iJN4nbi8AfgRYgCfgt8NcajeY3wBrgA+Dtfj4WEuQk5nCT4SY2H99Mt6Nb7XAk/dDt6OZI0xFV2iRBVNwudV5Szc8p2D3c+qLVaJmfOZ+9pr04nA6frFnRWEFrV+uIm29zkRWbRZ21DpvDpnYoiuPy31zz3hrOW87z2yW/5dkFz6LX6RXbc3H2YrQaLTvO7VBsj0DDbDHL+TaJxF3kfJtkGHicuDmdzn1Op3Oa0+mMdTqdy5xO52WEGEkJsNTpdLb09zFfBq02ayevxdRmothYrHYokn442XISq91KXrI6iZtLWVItgRKXomSoVJMWZCyguaPZZxWM3cbdhGnCmJcxzyfrBRuZsZk4nA7qLOpaVijNhfYLPLLzEZ4reY6ZqTPZfu92bh17q+L7JkUlMSt11oixBbDarFzsvBgSFX6JxC/I+TbJMPDJ7JnT6bzodDrfdDqddYN9LFRYOmYpqTGpUqQkQHEJk+Sn5Kuyv9qJWyh4uPVlfsZ8AHaf940twG7jbgpSC4iPiPfJesGGy8ut1lKrciTKYbQYWfnuSr42fc3P5vyM3y/7PakxqX7bv2hMETWXajh3+Zzf9lQL131Omm9LJG4i59skwyAkREP8jU6rY03uGvaa9nKm5Yza4UiuoaKpglGRo8iOy1Zlf7UTN1ObKaQSt9HRo5k2ehp7TMOfc2u0No5IG4C+uNRGQ1lZ8uPTH9Pc0cz/3Pk/PDT1IbQa/77VFY0pAhgRVTfXz5GsuEkkbiLn2yTDQCZuXvJA7gOEa8PZfGKz2qFIrqGisYLpydNVaxVMi0lDg0aVxM3SZaGlsyXkHqIWZC6gvLGcls7hdV332gBkjtzZgtSYVMK14SEtUFJiLiEnMYepo6eqsn9mbCZTkqaMCFsAlxCTrLhJJG5g64Dz38j5NonXyMTNS5Kjk7lt7G28XfM2VptV7XAkPbTZ2jh56aTfjbf7EhEWwejo0aooS4bq6XdhZiEOp4NSc+mw1ik2FpManUpuYq6PIgs+wrRhZOgzQtYSoLO7k0MNh5hrmKtqHEXZRZQ1lNHU3qRqHEpjspgI14STEh34XqwSieoYD4C9Q863SbxGJm7DYN2UdVhsFt4/9b7aoUh6ONJ0BCdO1RQlXaTr01WpuLk83DL1odMqCZCXnEecLm5Y7ZJ2h50SUwmFWSPTBqAvmbGhawlQ1lBGZ3cnN2eoOz9SNKYIJ06+qP1C1TiUxtRmIk2fRpg2TO1QJJLAR863SYaJTNyGQX5KPlOTprLx+MYRZbYayFQ0VQCopijpQi0vN1Nb6Jhv9yVcG868jHnsNu72+netvLGcVlvriG6TdJEVlxWyFbcScwnhmnBmp81WNY7cxFwyYzNDfs7NbDGH1EytRKIoZ4rlfJtkWMjEbRhoNBrWTVlHzaUa9tfvVzscCUJRcmz8WBIiE1SNw6A3UG+t93tCb7QYiQ6PJikqya/7+oOFmQtpsDZQfanaq9cXny8mXBPOvPSRaQPQl8zYTC51XsLSZVE7FJ9Tai4lLyVPUa82d9BoNBSNKaLEXEKbrU3VWJTE1GaS820SiTu45tvGyjZJiffIxG2Y3DH+DhIiE6Q1QADgdDqpbKpUvdoGYIgx0G5vH7aYhqeYLCYy9KHj4dYXly3AHqN37ZIuG4DYiFhfhhWUuCwBQk1ZsqWzhSMXjgRMcl6UXYTNYQtZz09bt41Ga2PIVfglEkWQ820SHyATt2ESFR7F/ZPuZ+e5ndS31asdzoim3lpPY3sjM1LUEyZxkR4rTqDrrP6dczNajCH7EJWmTyMnMcerxK2+rZ4TF0+wMEu2ScIVS4BQa5fcX7cfh9PB3HR1hUlczEydSWJkYsi2S9ZZ63DilBU3icQdXPNtY+V8m8R7ZOLmA9ZMXoPD6WBL1Ra1QxnRlDeWA6iqKOnCECO83MwW/865hXLiBlCYUciBhgMeK7m6RE1Gsn9bX1wVt/OtoZW4lZhLiA6PDoh7AAgFzyXZSyg+X4yt26Z2OD7HdX8L5XuOROIzzhSDIQ+iE9WORBLEyMTNB2THZbMoaxFbq7aG5JtzsFDZWEmENiIgpN7VqLhd7rpMa1drSAsFFGYWYnfYPbYF2G3cTWpMKjmjchSKLLiIj4gnVhcbcq2SJeYSbky7EV2YTu1QeikaU4TFZmFf3T61Q/E5vWJIepm4SSSDIv3bJD5CJm4+Yu2UtVzouMBnZz9TO5QRS2VTJVNHTw2Ih7akqCTCteF+VZZ0nX6HcuI2M3Um0eHRHtkC2Bw2vjZ9zcLMhSE5++cNGo1GWAKEUOJW11bHmctnAqZN0sW89HlEh0eHZLuk2WJGgwaD3qB2KBJJYCPn2yQ+QiZuPmJ+xnzGxI2RIiUqYXPYOHrhaEAIkwBoNVoMMQa/erm5HsJDOXHThemYmz7XI1uAsoYyLDaLtAG4hqy4rJBqlXRVYQNFmMRFVHgUhZmF7KrdhcPpUDscn2JqM5ESnRIQh2USSUAj59skPkImbj5Cq9GydspayhrLOHbhmNrhjDhqLtbQ0d0REMIkLgx6/yZuLvPtUJ83KcwoxGgxcvbyWbeu323cTbg2POAqMWrjqriFigdlibmEpKgkchIDrx22aEwRje2NVDZVqh2KTzFbzL1t4RKJZBDkfJvER8jEzYesmLSC6PBoNp3YpHYoIw7XA1GgVNwA0vXpfq+4RYdHMyoytI09F2QuAHC7XbLYWMys1FnSBuAasuKy6OzupKm9Se1Qho3T6aTUXMpcw1y0msB7W1uYuZBwTXjItUsaLUY53yaRDIWcb5P4kMB7hwti4iPiuWvCXXxw6gO/+3eNdCoaK0iKSgqoNkGD3kCDtYFuR7df9jNajGTGZob8HFdWXBbj4se55Y1V11ZH9cVqqSbZD67flVCYczvVcorG9kbmZQRWm6SLhMgEbjTcyM5zO0OmwulwOqiz1smKm0QyFHK+TeJDZOLmY9ZOXktndydvVb+ldigjisqmSmYkzwiopMWgN9Dt7KaxvdEv+5kspoBKXJWkMLOQ/XX76bB3DHqdy/NNzrddj8sSoLa1VuVIhk+JuQQgoNthbxlzC2cun+F0y2m1Q/EJjdZG7A67rLhJJENxdg9yvk3iK2Ti5mMmJ01mdtpsNp3Y5LdKy0jnctdlTrWcIi8lcNokgV6lNX+1S5osppCfb3OxIHMBnd2dHKg/MOh1xcZiDHoDE0dN9FNkwUMoVdxKzCVkx2UH9MHFkuwlAOysDY12SZdirqy4SSRDIOfbJD5EJm4KsHbKWowWo0eS5RLvOdx0GAis+TYQM27gn8TtctdlWm2h7eHWlxvTbiQyLJLdxt0DXmPrtlFiLqEwszCgKrGBQmRYJCnRKUGfuNkddvbX7Q/oahuIg5zpo6ez4+wOtUPxCS4xpJFyz5FIvMLeCbX75HybxGfIxE0BbhlzCynRKbxx/A21QxkRVDZWokHD9OTpaodyFa6Kmz+83EaKoqSLqPAobky7cdDDkbLGMtpsbbJNchBCwRLgyIUjWGyWgLMB6I9bxt7C4QuH/SpapBQu823XAZVEIukHOd8m8TEycVMAnVbH6smr2WPc47ZkucR7KpsqGZ8wnriIOLVDuYq4iDhidbF+eUgztoqqyUhJ3EDMuZ1uOT1gxaj4fLG0ARiCUDDhLjGVoEHDHMMctUMZkqLsIgB21e5SOZLhY7aYGRU5ihhdjNqhSCSBi/Rvk/gYmbgpxKqcVYRrwtl8YrPaoYQ0TqeTyqbKgGuTdGHQG/xSces139aPnLalXlsAY/9Vt2JjMbNTZ6PX6f0ZVlCRFZdFXVsdtm6b2qF4TWldKVOSppAYFfjzI+MTxjMuflxI2AKY2kyy2iaRDMWZYjBMl/NtEp8hEzeFSIlJYdnYZbxd/TZWm1XtcEIWo8VIc0dzQBlv98VfJtymNhN6nZ6EyATF9woUxsWPIzM2s985t7q2Omou1bAwS7ZJDkZmbCZOnH45XFACq81KWUNZULRJAmg0GorGFLG/bn/QW8aYLeYRVeGXSDxGzrdJFEAmbgqybuo6Wm2tfHD6A7VDCVkC0Xi7L/5K3IwWIxmxGSNKhEOj0bAgYwGl5tLrKkYujzfp3zY4WbHCEiBY59wONRzC5rAFVTts0Zgi7E47X53/Su1QvMbpdMqKm0QyFHK+TaIAMnFTkIKUAiYnTmbT8U0hY7oaaJQ1lBEVFkVOYo7aofRLuj6di50Xh/QbGy4mi2lEtUm6KMwsxGq3UtZYdtXHd5/fTYY+gwkJE1SKLDhwebmdtwRn4lZqLkWn1TEzdabaobhNXnIeKdEpQT3n1tLZQru9XVbcJJLBcM23jZHzbRLfIRM3BdFoNKybso6qi1UcbDiodjghR0VjBVuqtrAwayHh2nC1w+kXf3i5OZ3O3orbSGNO+hzCteG9FTaQNgCekBKdQrg2PGgFSkrMJRSkFgSVQIZWo2Vp9lJ2G3crfqCjFC5FSWm+LZEMgmu+LSZJ7UgkIYRM3BTmzgl3EhcRx8bjG9UOJaRoam/isV2PkRqTylPznlI7nAHp9XKzKpe4Xe66TJutbUQmbnqdnlmps64SKDnYcBCr3SrbJN0gTBtGZmxmULZKXuy4yPHm48w1BE+bpIuiMUW029spMZeoHYpXmC3SfFsiGRQ53yZRCJm4KUx0eDT3T7qfHWd30GBtUDuckMDWbePxLx7nctdlXlv6GqOiRqkd0oAYYnq83CzKiT+4qiWueaWRxoLMBVRdrOr9/dpt3I1OqwuquSc1CVZLgH11+3DiZF5GcAiT9GWOYQ6xutigVZd0/bzIiptEMgByvk2iEIHZXxZiPDj5Qf589M9srdrKDwp+oHY4Qc9L+17iUMMhfrXoV0xOmqx2OIOSpk8DlK24jTTz7WtZkLGA3x74LXuMe7g/536KzxczO222cu1zDgec+BC62sDpEH9wXvm709nnY86rP+bptRotzHwIEscp87UgEv4jF44otr5SlJhLiNXFMm30tOs/2W2Hms+hyyL+H/b9ow3r829Nn7+HXX+tRgvafj7We73m6nXo82/6+5z4o0PDwvSb+aJ2F93tLYSF6QZZo+dPAGFuMxMdHj2iVGwlEo+Q820ShZCJmx8YEz+GwsxCtlRt4bt530UXplM7pKBlW9U23qx6k7+d9rfcMf4OtcMZkoiwCEZHjVZ0xq339NvTxM3WAWER4sE0iMlNzCU1OpU9pj3MTZ/LyZaT3J9zv3IbHnsHtnxLufWB3gd2pwMunYWVf1Rsp8y4TFo6W2jtag04E/vBKDWXcqPhxv7nW3c8A3v/ye8xeUKRPoaPUpM59FoON3Z0Dv0CjRa0OtBFX/kTHg26KNDFQHjUMD4XI/4d3vN5bTg4bNDt+tMl/jjs0N2FqekoGRGJaM7s7uc6W8/HukQCfc1rr7rW2S0S4DCdSKi1OrG3x/8OF/8d6N+6KEjIDrgEWNIHW7v42QsVqj6B9Blyvk3ic2TiNhhfvQr1h2H1fw57qbVT1vLDHT9kx7kdLB+/fPixjUDKG8vZULqBm9Nv5tFZj6odjtuk69MVTdxMFhOxuljiI+Ldf5GtA35XALO/BUt+plhs/kCj0bAgcwGfn/uc2WmzAZT1byvfBHHp8K0Prq/aXFtluarS0l9lZqBrex4w330EKreJ6l6EMkbirhZbo8XIlKQpiuzha4wWI7WttTw09aHrP3lyl0jaZv41zP9Rn+pmd5+/96lsOq79+BB/eq939lnXyZVKaj9VVLjyuZ7rFnZ3ojv5X+yccgs3Js+5Zg36qcQ6REJka7/yx95x5e/Wpv4/7vC9ubo5w0B6dzf8190evlIjDovCIq4kVw67+H/abev5u0Jm8Cv+BWb+lTJrS4bHhZPwrzfDqv+AqZ7+TAUgTdVg3A+3Pa92JJIQRCZug+HohiNvw7JaGJU9rKUKMwvJis1i4/GNMnHzgkZrI4/teoy0mDReWfwKYdowtUNyG4PewMmWk4qt75WH24kPodUMB/4TFv1EnF4HMQsyF/BWzVv8x+H/IDM2k/Hx45XZqK1JtODN+wGMnqjMHn3JWwMH/xtOfAR5qxTZIjNO2EgYW4MncSs1lwJcb7xtbYa3vw/JuXDHryAicNUm9cC8jhp2tpziJwt+rJwCarcd7O3isMZm7UnqrOLf9vZ+EkGrSKDCIkTFKkzXk2j1/F2rw3RoAzOSZ8Ly9YNed9W/wyLcu8+4EtW+idy1iZ1H/7bDrhfg4J9l4haolP0Fujth/7+HRuJWsVkcxOWtVjsSSQgiE7fByF8LX7wAFZvEw+0w0Gq0rJ2yllf3v8qJ5hMBP5sVSLjESCw2C79f9vugm6sw6A3sMe3B6XQq8nBmtBh7/bjcpuwN8cbSaobTX8LEIp/H5U/mpc9Dq9FS11bHg5MfVO4h+PB28SCYv1aZ9a9l7AKIz4SKNxVL3HpNuIPIy63EVEJKdMrVPn1Op6hQtjXB+s0BnbS5KBpTRPHXxVRdrFLuPSEsHMLiINI3bbBWm5WWb35OesZNMH6RT9a8Co1GtE/68jCppRY+fwaaT0GS9HYMKBwOKO9JdE7ughYjJASxJ6nr65mwFOIMakcjCUGCe7hFaRLHCinXso09bSzD475J9xEVFiWtATzkxX0vUtZYxrMLniU3MVftcDzGoDfQbm/nctdln6/tdDoxWUyeKUq21sHJHaJqFJUgWv+CnITIBGYkzwBgYaaCbZIVmyAtD9L6EcRQAq1WJGw1n4uERAHiI+KJ08UFjSWAw+mgtK6Uuelzr07QD/wnHH8fbn0a0vNVi88TlmQvQYMmqNQlg1IMKW8NoBEHIJLA4uxuuHweljwJOEW1Kpg5txdazkH+OrUjkYQoMnEbioL10HxS+HEMk4TIBO6acBcfnPqAls4WHwQX+myt2sqWqi18e/q3WT4uOFtMe73cFJhza+lswWq3evYQVbFZtCLN/luYthKOvQedrT6Pzd/cNu42EiITuMlwkzIbNFULiecZa5RZfyDy1og5qiNvKbK8RqMhKy6LUy2nFFnf11RfrKa5o/nqNsnGKvj4CXHKPe+H6gXnIcnRyRSkFrDj3A61Q3Ebl/m2674WFCRkiupg+SafHMJKfEj5JoiMh/kPCwXGsjeC+3tUvhEiYmHKXWpHIglRZOI2FFPvBZ1e9GD7gLVT1tLR3cHbNW/7ZL1QpqyhjA2lG1iQsYAfzfyR2uF4jUHf4+XW5nsvN2Obh4qSTqeoIGfNgeRJ4lTQZhXJW5Dz0NSH+PSBT5WzAVBrbsEwHVKnKVotKMwsZH/9fkX9Bn2Fy7S616fP3gXb/k4o0t33b0GnklqUXcSJiyeCpuLp+hkJqoobiPbmi6d9cggr8RFdbXD0Hbhhhfj9zV8HF3oOyIIRWzsc6fl6gqBVWxKcBNc7nBpExopfwiNviV/KYTIlaQozU2ey+cRmHC61Mcl1NFgbePyLxzHEGHh50ctBJUZyLUpW3IytInHLjHVzJsB0CBqPiUoyQPYcSBwvTgmDHK1Gq6x3W8VmGL8Y4lWoNMxYDef3QfNpRZZ/IPcBnE4n22u2K7K+LykxlzAuflzvgQg7n4O6Cljxz+p8b4ZJ0RgxX7qrdpfKkbiHqc2ETqsjOTpZ7VA8Y+o9wvYgBO51IcPxD4TXoqutcNp9wpLCRwflfuf4B9DV6r8ZaMmIRCZu7lCwHjovi19KH7BuyjpqW2vZY9zjk/VCja7url4xkteKXgs6MZJrGR09mnBtuCIVN4/nTco3QlgkTOvxOdNoxJvm6WK4VOvz+EKG2hK4dE69N+TpPcIklVsUWT4zNpP5mfPZXrUdu8OuyB6+wNZt40D9gSttkqe+gL2/E22/QdqaNCZ+DJNGTQqadkmzxYxBb0CrCbLHh8g4mHI3HNkOdjd88yTKU74RRo25YlIdlSBUJQ9vE6qnwUb5JojPgrGFakciCWGC7M6rEmMXiJuLj06Bbh1zK8nRyVKkZABe3Pci5Y3lPLfguaAUI7kWrUZLWkyaMhU3i5G4iDj3PNzsneLBf+rdED3qysdnrAGcUCkH9wekYrM4rZ+iklT1qGxxH6p4U7H5j9W5q2lob6D4fLEi6/uCiqYK2u3tInGzNsNb3xPS/7e/oHZow6JoTBGHGg7R3NGsdihDYmozkaEPsjZJF/lroaMFqj5WOxLJZZM4eJmx9ur25oL1Pd+jj1QLzSta64XoV/6DQdeuLQku5E+XO2i1oirhkqodJrowHatyV7HbuJvay7LK0ZctVVvYWrWVv5v+d9w+7na1w/EZBr1BkcTN1GZyv02y6hNovwj566/+eNJ4GDNfDu4PhK1DtEpPvUe0TqvFjDVi/sNcpsjyi7IWkRKdwtbqrYqs7wtKzaVoNVpuTLvxivT/A38K+nmSW8bcgsPp4MvaL9UOZUjMFjPpscHXkgrAhCUQaxBy7RJ1qdwiRLKu7WIYvxjiMoRISTBxeKv4embINkmJssjEzV3y1+JLqdrVuasJ04Sx+YR8A3FR1lDGC6UvsCBzAY/MfETtcHxKuj5dmcTN4sHpd/lGiEuHiUuv/1z+WmiqAtNB3wYYClR/Ik6AZzyobhw3rBAmxhXKtEvqtDrum3Qfu427A1akpMRcwrTR00g48lbQSf8PxtSkqRj0hoC3Bejq7qKxvTF4K27aMGGvUf0JtF1QO5qRS1+RrNETr/6cNky8H9XsENY1wUL5RsiYBSnB3yUkCWxk4uYuSRNEq5KPpGpTY1K5ZewtbK/ZTrt9+KInwU6DtYHHvniMdH06Ly8MbjGS/jDoDdRb6+l2dPtsTafTidFidG++zdII1Z+Kqk1//2+n3Sdm30LA083nlG+G2DRxEqwm0YmQc5s42fXhz1FfAlmkpM3WRmVjJXMTcuuZAvIAACAASURBVHqk/5cElfT/YGg0Goqyi9hr2ovVZlU7nAGpa6vDiTN4K24gumccdjHrJlGHugohkjXQzHDBemGBEiy+e3WHoa5SerdJ/IJM3DzBJVV7fr9Plls7eS2tXa18dDrIerl9TFd3F4998RhttjZeWxr8YiT9ka5Pp9vZTVO770yUL3ZepN3e7l6rZOUW8bBybZuki6gEIe5QuVXIq0sE1maR8OathrBwtaMRcVjq4bQyLXW9IiXVgSdScqD+AHannXnHPoXwKLjv9yE1S3LLmFvocnSx17RX7VAGxOXhFrQVNxD2GmnT5SGVmpRvEt0DLpGsa0nOgaybRBUrGNr3KzaBNhymP6B2JJIRQOi86/mDafcJgQIfiZTMTptNTmIOG49vxBkMNycFcDqdvFD6AhWNFTy/4HlyEnPUDkkRXNLldVbftX64FCXdStzK3hBtHKlTBr4mfx20N0PNZz6KMAQ4vA0cNvXbJF3kLhdmtQq1SwKszllNgzXwREq+Nn1NJFoKTEeDVvp/MGalzSI+Ij6g1SVdLbRBXXEDUekx7oemarUjGXl028RBYu5yiEka+Lr8ddBwVLGZXp/h6Bb345zbQD9a7WgkIwCZuHlCZJww5D683SdStRqNhnVT1nG8+ThljQF+c1KILVVb2Fa9je/kfYfbxt2mdjiKoYQJt9Hipvm2uQLqK694tw3ExCLQp0ifo75UbIbUG8CQp3YkAl0U3HAvHHsXupRpqVuUHZgiJaVndzKz3UrkrOCV/h+McG04S7KX8OX5L7E5bGqH0y+mNhNajRZDjEHtUIZH3mrQaH02sy7xgJM7oa1x6LbC6StF+35ZgL8fnfoCLHXSu03iN2Ti5ikF66CzBU74xtPtrvF3EaeLG5HWAIcaDvHivhcpzCzk4YKH1Q5HUVyJW31bvc/WdNvDrXyjaEsZqo0jLBzy1sCJj0WL4Ejnwkk4/42otmk0akdzhbw1wrRWIbnsQBQpaWquptpqYp5GH/TS/4NRNKaI1q5W9tf5ph3f15gsJlKiU9CF6dQOZXjEGWDCUjG/6nCoHc3IonwjxIyGSbcOfl10Iky5U1TnArl9v3yTGDXIXa52JJIRgkzcPGXcImGw6COp2hhdDCsmreCzM59xpuWMT9YMBurb6nlslxAjeWnhSyEnRnItcbo49Dq9zytu8RHxxEXEDXxRt00MeA/VluIif61oDTy8zWdxBi0VbwIacTofSIwrFOqgCrZLBpRIidNJ6UePAjBv8dNBL/0/GPMz5hMVFhWw6pLmNrN7YkjBQP5aaDkH575WO5KRQ/slOP4hTF8F4RFDX1/wkGjfr/5E+di8obMVjr0nDkXDI9WORjJCkImbp2i1oup2cidc9s1D+Lenfxt9hJ4nip8I2BYZX9LV3cXjXzyO1W4NWTGSa9FoNBhifOvlZrQYh55vq/4MrE3iDdAdDHmQOk0O7jt7rD/GL4IEN33y/IVL0rzmM8UkzQNKpOTgf1F68Rjx2kim5N6rbiwKEx0ezfyM+eys3RmQc88mi4l0fZDPt7mYchdExMrWcH9y9G3o7nS/rXDCUqHoG6iebsfeA3u79G6T+BWZuHlD/jphtOij/viUmBSemvcUhy8c5g/lf/DJmoGK0+lkQ+kGKpoq2FC4IWTFSPrDEGvwacXNZDG50Sb5hphbm3SLe4tqNHJwH6B2H1w8HTiiJNeSt0aohB59S7EtAkKkpKka58dPUBI3ijlZhSFfmQfRLtlgbeDIhSNqh3IV3Y5u6tvqQ6fiFqEXM+tH3wGbtOTxC+WbIHkyZMx07/qwcHEPrv5UWNoEGuUbIXE8ZM9ROxLJCEImbt4weiJkz/OZpxvAbeNu496J9/J65euUNYSuUMmbJ95ke/V2vpv3XZaNXaZ2OH7FlxU3p9OJyWIavOJmbRbzajMeBE9mUmasEYP7I7nqVrEJwqOFEEggYsiDlCmKtkuqLlJi74Jt36E2Mgozdual36xOHH5mcdZiwjRhAdcu2djeiN1pD52KG0D+g9B5GU58qHYkoU/zKdGWmr/Ws5nhgvXikKpSuXudV1yqhdPF4iA/kGagJSGPTNy8pWA9NJ0A00GfLfnEnCdI16fz5O4nA9qE1VsO1h/kpX0vUZhZyA8LQsM41xPS9ek0dzTT2d057LWaO5rp6O4Y/PS7cquYV/PUFDTOIBQmK0bo4L69UyjHTrlLKMkGIhqNSLBrS+DiWUW2UF2kZNfzYC6j5Ka/AmBexjz/x6ACo6JGMTttdsAlbq5ugZCpuAGMWwjxmUKkRKIsrpnhGWs8e13qVFGhKw+wdsnKNwGn51+PRDJMZOLmLdPuEyfyPuy9jo2IZUPhBs63nudX3/zKZ+sGAnVtdTz+xeNkxmXy8qKXR0TL07X4UlnSLQ+3sr+AYYYwnPWU/HXQUgtn93gZYRBT/Rl0XAp8eWeXaIqCJ9GqiZSc+hL2/A5mf4sSZxsGvYExcWPcfrnD0c2Z8oMBOSfmDkVjijjZcjKgBKt6VWyD2Xz7WrRh4veo5nOwNKgdTejidIq2wvGLICHL89fnr4e6SvEnEHA6RUfKmJshabza0UhGGDJx85aoBJh6t6hq2IdfQXExO202357+bbZVb2PXuV0+W1dNOrs7efyLx2m3t/Pa0teIj4hXOyRVcLUY+WLOzdg2hIdbfY9x6VDebQMx+U6IiBuZ7ZIVm0CfKgbjA5lRY8SDQ8WbPmvZvhZVREqszfDW92D0JLqXPce+un3MS5+HxoN2pJp9X7PthaeoKgnOg4el2eJnb2dt4FTdXPct1wFUyJC/FpzdUklXSWpL4eIZz7s/XOStAq0ucDzdTIegqSrwD/ckIYlM3IZDwXpxMn/Ct35KPyz4IVOTpvLM18/Q1N7k07X9jdPpZEPJBiqbKnmh8AUmjpqodkiq4Xrg8cWcm7FVJG4DVtzK3wBtuPdS9hExMG2FUAFTyOg5IGm/CFWfiAeFsHC1oxmavNWiZbuuQrEtXCIlu427FdujF6cT3vuRMOhd9e8cb6ulpbOFuelzPVrGVHUcgIMfvatElIqTEZvB1KSpAdUuabKYSIxMJEYXYnYMqVMhPV+qSypJ+UbQxcDUe7x7fUwSTF4u2ve7A0B5u3yTMAe/4T61I5GMQGTiNhzGLxb98T6WqtWF6Xhx4Yu02dp4eu/TQdvuA7D5xGbeqnmLv5/x99wy1k1lwxAlTZ8G+KbiZrKYGBU5Cr1Of/0nu+2iCpNzO+iTvd8kf50wej7uG7P5oODIW9DdFbhqktcy7X5xEl3xpmJbLMpeRHJ0Mluq/CAOcPC/hcT2LU9Bej6l5lIA5qV7Nt9Wd7IKNBpMJ45SdzI41VGLxhRR3lhOozUw1PRMFhPpsSEkTNKX/HVgLoeG42pHEnrYOuDwW0LBMzLW+3Xy1wtrm5rPfRebN9i74PBWYQ4ePUrdWCQjEpm4DQdtmHjAq/kcWn3nzwUwcdREHpv9GF+d/8o/D0wKcKD+AC/ve5lFWYtGpBjJtUSGRZIUleSbilubceA2yVO7wFLvfZukizHzIWHMyDqJLt8s5KrT89WOxD1ikiBnmWjzcnQrsoVOq+P+SfcrL1LSVA0f/0wciN38MAAlphImjZpEcrT7BxDddjv1p04yfcmtRERHB23VrWhMEQC7agOjZd7UZgqt+ba+TF8FmjDRJi3xLVUfQWfL8NsKc5ZBTLKY3VaTms/BekF6t0lUQyZuw6VgveiPV+DEe92UddycfjOv7n81oIbU3aGvGMmLC19Eq5E/aiDm3HyRuA1qBVD2F4hOgpzbhreJVivksk/t8pnZfEDTfFqoNOY/GFzyznmrodUMZ5TzW3OJlLxVo5BvXI/0P+GRcP/vQauls7uTgw0HPa62XTh/DntXJ2PzCpi25FZO7C3GcrFZmbgVJGdUDtlx2QHRLul0OjFbzKFbcYtNgUm3ivfxkaikqyTlmyAuQwiTDIcwnVBwPPGxmINVi4pNIoF01xtVIvEx8ml6uCTnQNYcUZXwcUujVqPluQXPodPqeKL4CWyOAOjtdoPWrlYe3fUoHfaOES1G0h8G/fC93Fwebv2efrdfhOMfiof58Ihh7QOIU0WnI/A8dJTA9TXmBZm88+Q7hJCMgp5uLpGSbdXblBEp2bVBiOnc+88QL36uyxvK6ezu9LxNsqYKAMOkycxcfg8ORzflnwWfT5dGo6Eou4jSulJau1pVjeVi50U6ujsGV7ENdvIfhMtGRQ9ARhyWRqHSO2ON6FAaLgXrhcWNWkIy7ReFpkHeas+8USUSHyITN19QsA4aelT8fEyaPo2nbn6KwxcO88eKP/p8fV/T2tXK9z77HlXNVfxq0a9GtBhJf6Tr0zG3mYc1t3ih4wKd3Z39t0oe3g7dncNvk3SRPAmyblLkYCKgcMk7j1sIo7LVjsYzdD1G4cfeFfMkCqGYSMnpr2DPazD7W0Kpt4cScwlhmjBmp832aDlzTRVRcfEkpKaRaMhgwqybKP/0Q+xdXb6N2w8UjSnC7rD7RxhmEFwtsiFlvn0tk++EyPiRqaSrFIe3io4kX6kvGvIgLU+9dknXDLRUk5SoiEzcfMG0lUJhyMciJS5uH3c790y4h9crXqe8sVyRPXyBpcvC9z7/HkcvHOXXS37N4uzFaocUcBj0Bqx2K60270/QjZZBFCXLN0LqDb6d0cpfKw4mAsVDRwmMB6D5ZPCIklxL3mrovAxVHyu2hSIiJdZm2P6/YfQkuP2Fqz5Vai4lLzmP2AjPBA3qak6QPjGn1z5g9p0raG+9zLE9X/gqar+Rn5JPUlQSO87tUDUOU1uPh1somW9fiy4ablghDkC62tSOJjQoewPSC4Ryp68oWC/k+BuO+W5NdynfBClTgmcGWhKSyMTNF0SP6vF02+JTT7e+PDH3CdJi0nii+AmstsCTZ+9N2pqO8uqSV3sH6yVX47IEGI7Iw4Dm203VcP4b8cbmyxmtaSuFcmEon0SXb4LwKPHgFoyMXwSxBkXVJX0uUuJ0wnuPCun/B/4EEVcUUi93XebwhcPMy/CsTbKr3UrT+XMYJuX2fix72gySs8dy6MN3g06hN0wbxtLspRSfL6arW72KoeueE9IVNxCHVCNNSVcp6o8ImxJvvdsGIm+1sLpR6KB8QJpPCT+6/LXBNQMtCTlk4uYr8tdf8YBSgLiIODYUbuB863l+9c2vFNnDW9psbXz/8+9zpOkIry5+lVvGyKHdgXAlbvXWeq/XcFXcrjv9LntDKKP5ekbL5aFT+aawGgg17F1iZmLynRAVpPOY2jCY/gBUf6ro4P7KnJW+Eyk59GdR3bjlF5BRcNWnvqn7BofTwVyDZ/5t9adPgtNJ+qTJvR/TaDTMunMFjefOUHsk+KrGRWOKsNqtvdYIamBuM6PX6UN/XrlXSTeED6n8RfkmkWBNf8C368amCOGtCj+/H5VvBjTBNwMtCTlk4uYrJi6FuHRFT4FuNNzI307/W7ZVb2PXucCQiG6ztfG9z75HZVMlryx+ZcR7tQ2F68R6uBW364xwHd3ijXLSrRCXNtwwryd/naiMnFRf4c7n1HwO7c3B2ybpYsYaMbh/9B3FtsiKy2J+hg9ESppq4KOf9kj/P3Ldp0vNpUSHR5Of4llLkkuYJG1izlUfn1K4mKi4+KC0BpibPpeY8BhV2yVNFhPp+vTe9tOQRasVv0endvnc4mdE4ehR2p60TCRaviZ/HVjqxPfJHzidYgxhwmJICGGBHklQIBM3X+HydKv+FCwNim3zcMHDTEmawjNfP0NTe5Ni+7iDq9LmStpuHXurqvEEA6OjRhOuCafO6v1Dgcliur7advpLaDUJoRwlmLRMWAyEoqdbxebQkHdOz4fkXMUVQFfnDlOkxN4F2/7uKun/aykxlzArbRY6D5Xb6mqqSEgzEBOfcNXHdRGR5N96BycPlHKpLrisLSLDIinMLGRX7S66FfLqGwpzmzm059v6kj+ClHSV4tQXIrFSSsQjd7l4P/JXu+S5Erh01vdtnxKJF8jEzZe4PN0UvOHrwnS8WPgili4Lz+x9RrWZjTZbGz/4/AdUNFbwq0W/YtnYZVdfUPEmmCtUiS2QCdOGkaZPw9zm/cOj0dKP+XbZGxA1CnLvGGaEAxAeAXmrxOxH+yVl9lCD9ktC3nn6A8Ev76zpaeM5uwcunVNsG5dIydaqrd4t0Cv9/0+90v99qW+r53TLaW5Ov9njpc01VRgm5vb7uYLb7kSr1XLok/c9XldtbhlzC80dzVQ2qdPq6aq4jQiScyBztmyXHA7lmyAqQSRYSnDV+9FFZfboS8Um0MXAlLuHvlYiURiZuPmSlMnihq/wKdCkxEk8Nvsxvjz/JVurvXx4GgZWm5UffP4DyhvLeXnRy9w27hqj5+MfwPbvwl9WQdsFv8cX6KTFpHnt5eZwOjBZTGTFZl35YEcLHHtfJB+6KB9F2Q/5a4XVgIKteH7n6Dvia8oP8jZJF3mrxH8rlbsvuERKio3Fnv8cu6T/Z/0NTL2n30tK68Qsl6f+bZaLzbReaLxqvq0vsUmjyZ1XyOFdn9JpDTyBp8FYmLWQcG04n5xRZoZ6MNpsbVzuujxyKm4gKiv1h6HusNqRBB+drXDsPSFqpeT7UcF6ce8+4oN528GwdcDht2DqvRDpmcKtRKIEMnHzNQXrxQ1f4WrT+qnrmZc+j1e+eYUzLWcU3asvVpuV73/+fcoby3lp0UvcPu72qy9orYd3HxEtW+0X4b0fhbb/lxekx6Z7nbhdaL9Al6Pr6oeoI2+DvR0KHvJRhAOQMUt8X0PpJLpiM4zOEV9bKJA0HrLnKt7m5RIp2V693f0X9Ur/T4TlLw54WYmphMTIRHIScwa8pj/qTlYDXKUoeS2z7ryXrvZ2jnz5uUdrq01cRBzLxi5j04lNHL1w1K97uxQlM/QjKHGbtlIIa1SE0L3OXxx9V7wfKd1WmF4AKVOVb5es+gg6W6R3myRgkImbr5m2EsIiFL+ZaDVanl/wPDqtjid3P4nNYVN0P+iptO0QlbaXFr7E8nHXtEE4nfDOD6DLCg/+BW55Co6/Dwf/W/HYgglDjIF6a71X8yr9KkqWbxQJVabCyYdGI968zu2F5tPK7uUPLp4VbYX5D4aWvHPe6h7fPeWqBS6Rku3V290TKXE6xSFOWyM88O9XSf9ffZmTUnMpc9PnotV49vZUV1OFRqsldfyEAa9JnzSZ9NwpHProPRwqzYt5y5NzniQpMomffvVT2u3tftu31wogdoS0SgLoR0PO7VCxRQhtSNynfCMkjofsOcruo9GIg/Lz3wgrHKUo3wRxGcJyRSIJAGTi5mtikoSseOWbYghfQdL0afzi5l9Q2VTJ6xWvK7qX1Wblhzt+yKGGQyJpG99P7/q+14VC323PQUouzPuhUI37+GdCRU4CCGVJu8POhQ7P20iv83C7cBLOfS1ON/2RfMx4ENCISlWwU9njeRZq8s691QJlv0erc1dTb613T6Tk4H+L9ql+pP/7crrlNA3tDcxN98wGAKDuZBUpY8aji4gc9LrZd67gUr2Z04f2e7yHmoyKGsWGhRs4e/ksr3zzit/27TXfHkkVNxAHOpY6IbQhcY9L5+BMsR/fj9aARqvcQbmlUTzTzFgtBOgkkgBAJm5KUPAQWC8IhUmFWT5uOXdPuJs/VvyRikZl2jOtNisP73yYgw0HB07aGo7DZ78Q/io3fUd8TKuF+/5NVCC3fxe6la8KBgMuLzdv2iVdFbdeoYDyTeKNy19tHAlZ4uSxfGNwt8A6nUJAZ8x8SByrdjS+RT9a2EIc3gYOh2LbuC1S0lQtDm8GkP7vS4m5BPB8vs3pcFBXU4Vh0tDtlZNuupnY0ckc/DD4ZjXnpc/jW9O+xZaqLew85x9rDrPFjE6rY3T0aL/sFzDkLhcCG6HUGq40FT2HYTP8dBgWZxD3uorNylRGD28Dhx1myDZJSeAgEzclmFgEsWl+k05/cu6TpMak8kTxE1htvh26b7e388jORzhQf4AXC1/kjvH9qBbaO2H7dyAiFlb8y9UnbQmZcM9rYDoIX7zk09iCFVfi5o2ypNFiJCkqSXi4ORw93jJL+lXnU4z8dXDxDNSqZwg8bEyHoKkqdERJriVvNVw2ilZQhXBLpMTeBdu+M6j0f19KzCVkxWaRFZc16HXXcrHORKe1bUBhkr6EhYcz8/a7OXe4gsazwdfy+8jMR5iaNJWn9z5Ng1U56xkXpjZhP+Jp62rQEx4pqtfH3xeCG5LBcTpFkjtmvpi19Rf568S97vSXvl+7fKOwWUm7wfdrSyReMsLuxH4iLFycOFV9DG3Ke63FRcSxoXADta21vLLfdy007fZ2Ht7xMPvr9/NC4QvcOeHO/i/ctQHqKmHFP0Ns6vWfn3afqELu/g2c/dpn8QUrw6m4mSymK22SZ3dDS63yoiTXMvUeIY0czJ5uFZshLBJuuE/tSJRh8p3iIMXVDqoQQ4qU7Hq+R/r/n4c8XLA77HxT9413bZI9xtuDCZP0Je+W2wmPiOTgR+95vJfa6MJ0vLToJTrsHfzj7n/E4VSuqgqi4jZirACuJX8t2KyizVcyOMaDcKHa/yIek+8UldEyH78fNRwX9y7p3SYJMGTiphT560WJ3U8mnjcZbuJb077F1qqtfFH7xbDXa7e388iOR9hfv58NhRu4a8Jd/V94uhj2/A5m/y1MHsRD7I6XYdQY2P73Qr5+BBMfEU9MeIx3iVtbH/Ptso0QGQ9TBvjeKEVkrJBGPvyWkEoONrptQi5/8nKIHqV2NMoQ0eM5dOQdRb9Hg4qUnPryyr1h6tD+R0cvHMViszAvw7M2SRD+bbqoaJIy3avURcfGccOipRzbvQvr5eC7H01ImMBPbvoJX5u/5s9H/6zoXlfdc0Ya2XMhcZxsl3SH8o3iMGyanw/DdFHCCufYe9Bx2XfrVmwCTRhMX+W7NSUSHyATN6VIuwEyZiovVduHh2c+zOTEyTy992kutHvvn+Zqj9xXt4/nFzzP3RMGeOhqvwhv9ch7375h8EUj42Dln0RLw4c/8Tq2UECj0WDQGzxO3FwebhmxGdBpER5k0+4HXbRCkQ5C/lohkVz1kf/3Hi4nd4K1KfTnFmasEd8jhWdtV+Wuul6kxNos7g3JOXD7C26t45pvm2vwTpjEMGESWg8EBGbdcS/dNhsVn3/s8X6BwOrc1SzNXsprB1/jePNxRfbo7O6kqb1p5FbcNBpxnzj9FbQY1Y4mcLF3weGt4hAxKsH/+xc8JCwIjr7tm/Uc3WJeb9KtEJvimzUlEh8hEzclyV8PdRWijdAPRIRF8OLCF7F0WXhm7zM4vRCP6LB38KOdP2KfeR8bCjdwz8T+TXJxOuGDfwBLPax8fUB576vIvgkW/1/RpqagQXAwkK5P93jGram9CZvDRqY+E469C7Y2IYesBuMXCYnkYDyJLt8E0UniTTmUGb8Y9KmKt0suzl58tUiJ0ym8HNua4IE/ieqfG5SaS5mSNIXEqESP9rfbbDSeOeV2m6SL0VljGDtjJmWffkC3PfiEkzQaDb+c/0tGRY5SzCLAdbg0Yitu0DMH61T89yioqf5UHOSq1VaYOVv4cfqqXfJMsThklt5tkgBEJm5KkrcKtDrf914PQk5iDj+e/WO+OP8FW6s9S45cSVupuZTnC58fOGkD0QJ6eBss+Zln/mEL/w9kzYH3H4dLtR7FF0p4U3G7ysOt7A1ImiBaedRAGyYqOtWfCcnkYKGjBU58CNNXQniE2tEoS1i4aCGq+gTaLym2zXUiJQf+Uwg63Pq0GOx3g3Z7O4caDnmsJgnQePYU3Xa7W8Ik1zL7zhW0XWymqkQ5ERclSYxK5PnC5znVcopf7/+1z9fv9XAbqRU3uHKfLd8U3Eq6SlK+EfQpQphNDVyebuf2QvOp4a9XvgkiEwYf/5BIVEImbkoSkyR+8Svf9KsU/kNTH2Ju+lxe+eYVzl4+69ZrOuwdPLrrUUrMJTy34DnunXjvwBdfPCuqbdnzoPBxz4ILC4eVfwRnN7z1vRFrbmrQG7jQcYGubve9/lyJW6ZD0+OVs15d4+j8teL7eDiIqqfH3gN7R+i3SbqYsRq6u0RbrYL0ipSUvQ4fPwETlgofRzc5VH8Im8PmF2GSvozLn0VieiYHP3zHqw6FQGB+xnz+1w3/i80nNvtkvrkvrq6AEV1xA3GvazwO5nK1Iwk8rM3icChvjXh/VwuXx+hwu0C62uDouzBthTpjCBLJEMjETWkK1kNbj4mjn9BqtDy/4HnCteE8Wfzk9aIB19DZ3cmPd/2Yr01f8+yCZ1kxacXAFzt6Ei6nE1b+wTtTyqTxcMevhCri3t95/voQwKUsWd9W7/ZrXKffGTVfAhr12zhSp0J6QXCpS5ZvgqSJkHWj2pH4h4xZMHqS4iJJWXFZzE+fx/aqLdh10cK/cQjp/76U1JUQrg1nVqoH1fse6mqq0CcmEZvkuc+YRqtl1h33UneyGnO1MnNi/uDRWY8yOXEyT+15iqZ23ykZmywmtBotqTH9qAWPJKbdL/xIg7E1XGkObwOHTf33o4RMmLhUdDgNx7/y2PtiDEGqSUoCFJm4Kc2kW0ULQdlf/LqtQW/gqXlPUdFUwesVrw94XWd3J4/ufJS9pr38cv4vuW/SEIpQe/6faEe461WhtuUtBevhhhWw83nhqTXCcLUeeTLnZrKYGB01mqjKN2H8QhiVrVR47pO/TpxC1x9VO5KhaTkPZ3aLk1k1K5X+RKMRJ+FndouvX0FWtdup1zrZs+hhiPesta7EVEJBSoHwJ/QQc00Vhom5aLz8nt6wuIjIGD0HPnzXq9cHAhFhEby86GWsdqtPLQLMbWZSY1LRaXU+WS9oiU6E3NtFd0H34AehI47yTZA6DQx5akciulBazg3Pv7J8I4waKzqKJJIARCZuShOmEw+KJz4WN7soqQAAIABJREFULQV+ZPn45dw14S7+UPEHKhorrvt8Z3cnj+66krTdn3P/4AuaDsGuF8Tp44xhGhdrNHD3/xPiCdu+C12+NQ4PdHq93Kzuz7kZLUYydfHC/Nrf3m0DMf0B0IYL6eRAp+JNwClm80YSeasQ4goKtrSe3MXiQ9tI1kSwxeqZqfWljkscbz7uVZtkh8XCRbORdC/aJF1EREWTd8vtVJfu4XJTEM1rXsPEURP5yY0/YY9pD3855puDQpPFRIZ+hLdJushfJ7pnTu5UO5LAoakajPtFtS0QDsOm3CUscrxV875sglNfiK/Hg44BicSfyJ9Mf5C/TrQSqKCk+OTcJ0mJSeHJ3U9itV1JjlztkXuMe9xL2rqsIsGKTYO7f+ubm3RMEtz/e7hQA5/+fPjrBRFpMWmAMLd1F5PFREaHRRgrTx1EOMafxKbApGUiKQrkeUWnU6iZZs8TrbojidETIesm5dol2y7AW99DlzyZ+6euvyJS4ib76vbhxOmVMEndqWrAu/m2vsy8/W5wQtmnHwxrHbVZM3kNS7KW8NsDv+VE84lhr2eymEiPHcHCJH2ZtEyo0QZTa7jSlG8CjTZwDsMiYoSP3NF3hGWOp/Qe7g3zYFoiURCZuPkDw3QwzPB7uyQIs+cXCl/g3OVzvLr/VQC6urt4bNdj7Dbudi9pA/j0H0WCdd+/ibYRXzFhMcx/GPb/B5wIQk8wL4kKjyIpKsntilu3oxtTm4nM5nOixdQd+wV/kb8WWs1w+ku1IxkYc7kQF8gfoW/IeWug/rDvW1qdTnj3YWhvhlX/zsopDwqRkurtbi9RYi5Br9MzPXm6x9v3CpNMzPH4tX2JT0ll0px5VH7+MbaOIDSV70Gj0fDLBb8kPiKen371Uzrs3n8tdoedemu9rLi5CI8QHQYnPhTqtCMdh0Mchk0sgjiD2tFcIX+9mFE75mHrs9MpEtGsOeKwSyIJUGTi5i8KHgJzmSqzQDcZbuJvpv0NW6q28NnZz/jxrh9TbCzm6ZufZmXOyqEXOPEx7P93kWBNWOz7AIt+Ifrj33kYLA2+Xz9AMegNbs+4NbY3YnfYyehsV8+7bSBylwvT1UAe3K94U4gL3DDEDGeoMu1+0IT53otq/3+IB9lbnwFDnhApyZjP9urtQ4oiuSg1l3JT2k2Eaz1XpKs7WUVSRhaRMcM/yJh15wo62iwcLd417LXUJCkqiQ2FGzjZcpLfHPiN1+s0WhvpdnbLiltf8tcKVVqFVVqDgrN7oKU28EQ8xsyDxPGet0vWVUDjMfVFViSSIZCJm7/IWyVmgcq97L0eJo/MfITcxFwe/+Jxio3FPHXzU6zKXTX0Cy0N8M4PIS1PJFhKEB4JK/8EXRaxV5DKcnuKIcbgtqqkS1EyMzIJxsxXMizP0UXBtJVCar+zVe1orqfbLtoEc24T7bkjkdgej6WKLcNTXOtL4wn45Odi3bnf7/3wqtxV1Fvr2WMcWiDAaDFyrvUc8zI8b5N0Op2Yq08Mu03SRebkG0gdP5GDH70btNYALhZkLuCvpv4VG49v5KvzX3m1hqmt556jz/RlaMFN5myh0lq+We1I1Kd8E0TEweQ71Y7kalyebmeKhXWRu5RvEod709zoQJJIVEQmbv5CnywqE+WbVVGligiL4MWFL5IZm8lTNz/F6tzVQ7/I6RRVsM5WeOB1kWApReoUWPYcVH8K3/xJuX0CCE8qbsbGwwBk5N4dmEPT+evAZhXJW6Bx6gtoa5AnqTMehMvn4dzXw1/L3glb/07MlFwj/b84ezHJ0clsqRp6pq7UXArAXIPnwiStFxqxtlzyyni7PzQaDbPvXEGzsZazFcGvdPvj2T8mNzGXX+z5hVcWAb3m27LidgWNRnhAnt3tWVIQanRZ4ejbwusswnMlWMVx3esr3EywXYd7ubeP3MM9SdAQgE+AIUzBevEAeXKHKtvnJuby8QMfu5e0gWiDqv4Elj0rPLuUZs53xQD4p/8IDcHrqeQu6fp02mxttHYNXaUynfxMvGbm3ygdlndkzxHtKYE4uF+xCaJGiYrbSGbKnaDT+6ZdcsezUF8JK/71uvkWnVbH/ZPud0ukpMRcQnJ0MhNHeT5TMhzj7YHIvXkhMQmjOPhh8LfCRYZF8vLCl2mztfGLPb/wuIroOlRyWZdIenAJcfi67TiYOP6B6JAJtDZJF6PGwLiFol3SnZ/7kzuFYmigfj0SSR9k4uZPcm6DmGTvpWr9SWNVTxvULTDn7/2zp0YDK/5FCG9s+4441Q9hXJYAQ1bdnE6MDRUkO7VEpUzxQ2ReoNGIN73TxXCpVu1ortDZKgxVp69UtmIcDETohVz2kbeH97tVswO+/me46TsweXm/l6zMWYnT6eSt6rcGXMbpdFJqLmVu+lyvPNjMNVWEhYeTMnacx68diHCdjoLb7uJ02QGaTcr63vmDSYmTeHz24+w27uaN456975gsJpKikogKj1IouiAlcSyMXSBa64K8pdZryjdCwpjAa9vvS8FDcPE0nCsZ+tryjUIxdNIy5eOSSIaJTNz8SZgO8laLYX4/e7p5hL0Ltn8HdNFw37/6tzUvLk0kb/WVsPM5/+2rAr1ebkNJp5//BlO3lUx9ACl39Uf+gwi/sAA6iT72HtjbRXuTRFQLOi5B9Wfevb6tCd7+PqRMgdueH/Ayl0jJtuptA4qUVF+qprmj2SsbABDCJKnjJhIW7ltz6PxldxAWHs7BjwKn7dfW2cFH//Ib9r3juaXMuinrWJi5kN/s/w1VF6vcfp25zSwVJQdixoNCZdl4UO1I/M9lM5zaJe73gdi272LqPaLDYCg17/ZLooKYt0ooh0okAU4A/9aFKAXrobsLDm9TO5KB+fIlIZ9+7+/UkfmdfAfc+G3Y+89wKoAl5oeJ24lb2RsYdToykqf5IaphkDgu8E6iKzaLuLLnqB1JYDBhqaj6e5NcO51CPKj9Ijzw7+JgZxCGEikpMYmTcG8SN4ejm/qTNT5tk3QRkzCKKQuWcOTLz+mweOEF5WM6rW1se+Fpjn61kz2b/4dL9e575IGY3XtuwXPERsTy069+Sme3e9VW6eE2CNPug7DIwGwNV5rKLeB0BP5hWGSs+D4deVvM5A3E0XeguzPwvx6JpAeZuPmb9BlCoTFQb/hn90Lxb2DmX6tr8nzbBqHe9db3Ars6OQxSolMI04QNnrjZOug+vJ268HAyE8b6LzhvyV8LTVVgCoCT6MsmkfjPeNA3hvGhQFh4jxfVx557UX3zJ6j6GG79pfCmHAKXSMnWqv6rRCXmEsbFj+s9wPCEC+drsXV2kK5A4gYw6857sXd2UrnrU0XWdxfr5RbefPZJzNXHWfqtv0cbFsaezX/2eJ3R0aN5fsHz1Fyq4bcHfjvk9U6nk7q2OllxG4ioBDEzenib6FAZKTid4tkl6yZInqR2NEOTvw66WuH4+wNfU7EZRudA5iz/xSWRDAOZuKlBwTowHgg8AY6OFtj+v0WFYvlL6sYSESOULNsa4P3HAqeC40PCtGGkxqQOPuN24gMa7RbsOMmIDYKHqBtWQHhUYHi6VW4BnCJxk1xhxhpxwuyJAmjDMSEaNOlWmPs9t17iEin5yvjVdYcTNoeN/fX7mZvuuZokKCNM0pfUcRPIumE6hz5+D0d3tyJ7DEVrcxObn/kZzedrWfF//pFZd9zLrDvu4fieL2k4c8rj9RZmLeShqQ/xl2N/ofh88aDXNnc009HdIStug5G/ThjP13jZdhyM1FVCw9HgUegdu0AIlQykK3DxjPCjy18rD/ckQYNM3NQgb42qnm4D8uFP4LIRHviTaDNQm4yZsPTnQnY4UCuUwyRdnz54xa1sI8YE8fAUFH5KUQlCAKNyq/on0eWbxcnwaM8VC0OazNlCAdRdqWxbhxALioi9Tvp/KFbmrMThdFwnUlLZWEm7vd37+baaKiL1ekYZlDvMmHXnClqbGqnZ74a4gY+5VF/H5qd/SuuFJlY++UsmzLoJgJtWrCJKH8vujf/l1bqPzX6MSaMm8Ys9v+BC+4UBr3MdJsmK2yBMLBJtx4FwSOUvyjeBVid8O4MBrVYk2Ke+gJZ+xIYqelrG5eGeJIiQiZsaxKYIhcmKN8GhzmnudVRuFQ9yi38KWTeqHc0VFjwqTs0+/Ak0n1Y7Gp+Tpk8buOJ22Qwnd2AcJx5uM+OCIHGDKyfR1Sq2mdVVQsMR+YbcHxqN+P9yuli0kw7Fjl9C/WEhVBSb6tFWfUVKuvvc60rNpWjQcJPhJk+jB8B8sgrDxFyv1CjdZeLsOSSkpvndGqCp9iybnv6/dFqtrPnFBrJvyOv9XJQ+ljn3reZ02QFqj1Z6vHZkWCQvL3qZ1q5Wntr71IAWAS4Pt6Co8quFS2ys6mMx9xnqdNvFbOzk5cHldZa/FnBef1DlavsctxBGZasSmkTiDTJxU4v8ddBqhpO71I5EnER98DhkzYGF/6B2NFejDYP7/wCaMNj+96qYlytJuj6dems9Dqfj+k9WvglOB8aUCb3XBgUTloI+Vd0qqetkePoD6sUQyMxYAziHFkmq/hxK/lVYguTe7tVWq3NXU2+tZ7dxd+/HSswlTBs9jYTIBI/Xs3V20HTujGLzbS602jBmLr8H4/Gj1J+qUXQvF3U1VWx+5mcAPPj0i/22ghYsv5vYpNEU/+U/PfZmA+Hn+fiNj/PV+a/YdKL/apE033aT/AeF2NiRgW0vQoZg9TpLmiBsC8o2Xj1ycX4/NJ8KnrZPiaQHmbipRe5y4RsylFSt0jgcQgDE0Q0r/yDECwKNUdlw92/g/D4o/rXa0fgUg96A3WG/vm3J6RR9+VlzMDk6SI1OJSIsSKSKw8JFYlD1iTrCMo5uUUHOuS24Tob9yeiJkDHrSqtQf1gahfR/6g2w7Fmvt1qcvZjRUaN7RUqsNisVjRVez7fVnz6J0+HAMGmy1zG5y/Sly9BFRful6lZ7tJItz/+ciOgY1j7zMsljxvV7nS4ikptXrcdcc8LrNs71U9azIHMBv97/a2ouXp+UmtpMxOpiiY+I92r9EUN6gbDGKHez7TiYCWavs4L1cKFaJGsuyjdCeDRMvVe9uCQSL5CJm1qER4g2i+MfqNtm8fU/wZliuONlcTIVqOStErOBX74Mtd+oHY3PcFXRrptzMx2CxuNQsB6TxRR8LUv5a8FhU8f24vSXYKnr8ZWTDMiMB6Guon+RJKcT3vmBECx64E9DSv8Phk6r4/6cKyIl++v3Y3famZfh/XwbgGFijtcxuUtkjJ7pS27l+N5i2i4pd58+degbtr/wNLFJyax99mVGGQavdE1fcitJGVns3vjfXomnaDQanl/wPHqdnp8WX28RYLaYZbXNHVxtx7UlonoTqgS719kNK0SS5tIVsHeK96apd0OUPJyQBBcycVOTgnVC3U2tNgtzBex4Tsj+FzykTgyecNerEJ8pzME7W9WOxie4pNCvm3Mre0P4BE27H6PFGHyJmyEP0qarM7hfvhkiEyDHu9a+EcP0laIFuT9Pt32vixnFZc9C2vD9Ax/IeaBXpKTEXEKENoKClAKv1qqrqSI+JRX9qMRhx+UOM5ffjcPRTdmnHyqy/vG9X/HOK8+TlJXNg8+8RFxS8pCv0YaFUbj2f9FsrOXIVzu82jc5OpnnFjxH1cUqXjv42lWfM7WZpDCJu8xYA2gGr14HOy6vs2BtK4yKhxvuFcmarUN0g3Rckt5tkqBEJm5qkl4g2pAGkqpVElu7UIqLGQ33/C44pHCjEmDlH+HSOfjoZ2pH4xP6rbjZO+HwVph6N/bIWOra6siMDRJhkr7krwXjfmiq9t+eXW1C5n7afaCL8t++wUhsKkxY0mOo22f2o/5oj/T/Mpj7v32yVV+Rkq9NXzMzbSZR4d59f8w1QpjEXySmZzJh5o1UfP4R9i7fKqVW7PiED373Cuk5k1nz1AvExLs/8zdpzs0YJuWyd8sb2LrcM9W+lkVZi1g7eS1/Pvpn9hr39n7cbDEH32GRWiRkwfiF4pAqBG1rAPG1JeeK9upgJX+d6CA48aEQKolNE/c/iSTIkImbmmg0ovf6/Df+fbgF+OxpaDoB9/9bcM0Bjb0ZCh+Hsv8Rp4BBTnxEPNHh0dRZ+yRuLpWy/PU0WBvodnYHZ+KWtxo0Wv9W3Y69D7a24D0Z9jcz1oiDkNpS8W9bB2z7O3FCfd+/+vRAxyVSUnOpxmsbAGvLJS431ivm3zYQs+5cgbXlEsf3fuWzNfe//xaf/fGfGJc/iweefJbIGL1Hr9doNCxc9y0sF5oo/+QDr+P4hxv/gYkJE/n5np/T3NFMa1crrbZWWXHzhBlr4eJpqN2ndiS+p/k0nNsb/F5n4xdBfBaU/JuouOWtDsyZfolkCGTipjZ5a0S7kj+rbtWfw74/wLwfCC+aYGPJz8TJ37s/ck/OPIDRaDQY9IarK25lGyEuHSYuxWgxAkEqyx1nED9fFZuFCI4/qNgkDFezvUsMRhxT7gZdzBWp7M+fFga7K/4/e3ce30S5/Q/8M9lmkklaWrqyry6sigiKgIiIiiyKqKgI7oLrvehVUdSfy3W73utyvwpu1xX3BXFDQPZFAUFZpSxCF9rSFkozk8xkm98faUKB0iZpkplJzvv14gWmSeaxbWbmPOd5zom+9H9zQkVKAMTev213cIIr0RUlj9WhV1/ktO+IDT/Oi6mSY0OKomDVZ3Ow7IO3cdLAc3DpP2bCzMaWfezQqw869e2HX+d+DtklxvQenInDc0Ofw2H5MB5b9RhVlIxFj7H1e6hSsN/ops8AMMF7FT0zGIP7nkvXBvdf6606JiH1KHBTmyMf6DYC2PgBsPifwMoXg/tLfv8omFHatQjYtya4H61mN+CsBGQh9hthsTpYdCCvB3D+Y/H9f0kWoxkY/2awDPPXU5MXFLRUIBDMpNXsDs7M7pgPbJyDAo8HFfvXA/PuAj65Nri3qM+VgMEYvonSZcYNCF4cD5cA+1Yl/ljOimCj1T5XRdUkOq2xduDkUcF9tn9+D/w6Gxg4FThpZNwPZTaYManHJLS1t8Wp2afG9B7lu4rAMAbkd+4W59E1jWEYnH7xWFTt3YPS7Vtifh8lEMDS997EL19+jF7nXYBL/nY/jCZzi8Y2+OopkAQn1s2LvRDQydkn4+9n/B1LS5fivxv/C4Cab0eFdQQLXWz9KrjUPVWEep11TpFeZ32vCf6d3wso6KXuWAiJEeWJteCsqcDn1wPL/wUgitlcsw2w8PV/7Mf/t4UHLLYG/+aD+3/ch4BJX+l7D1BON+CiZ4Bv7wkGPPk9AKMFMLHBoh4mC2DiIn/MYIpuGUggAMiHg+XuXTUN/q7/4z54/NfcB4FG+rUV5mRjudUK7F8QXLbaeShw5s0Agv2UGDDhIia6c/IowOIAvvsbkNUZUPzBcv1KoP7v+v8O+Or/HWjwnMae62v89Yr/yPeWmm5Hp8+VwT2Vn00B8noCIx5P2KFu6nUTbup1U8yNsyt2FyGnfQeYueSfu04dMgwrPn4PG3745qim2JEKBPxY8Pp/sXXpIvQbNQ7DrrsJTBwmGPI7d8XJg4bit++/wWkXjoY9K7al79eeei1Wlq3EstJlACjjFrW+E4P7RVe/EpwY9cnByUWfXP9vucFjEuDz1D9W/9+hf4ee1/D1jT2m+IOrdQzGY/421F/PYnyMMQYfNxgBvze4BPTc+9X+7sZHTjdg6D+AdmeqPRJCYkaBmxZ0HQ48WByc3fJJwQILHqH+72P/1D/udTXynPr/Fg4c/TWf++jjXfRsasw29ZsSzEb+/mEc3oxpIsCr/xtMMOhtIggDEGz8bGsdDMJsrYG8U4L9b2ytG/zJDn+9YPdcVG99G56//35cr7YyoQy5tlz99HA7lsUWvOhv/gxwVTdyo2EO/n3UDYShkZuRxm5QGjw39PrszkBO4svEp5Suw4O/k7JQX/o/cUFRrAEbEFxiWLGrCN0HnB3HEUXObGHRd8RF+HXu56itrECr/MgnU/w+L3545QUU/boKZ0+4GmdPuKZF34tjnXPVJOz8dRV++fITjLj59pjew8AY8NQ5T+HyeZfD5XOFl7WSCHUeFqx6vPip5p9rZI++tjS89oS+ZuObuB5xwfPeURNagaYnwsKPNZj4OvYxn+f4xzoNSa1eZ8Nnqj0CQlqEAjctYZhgvySzFeCbLwkdsYC/PtATg8FhRorMpDJMsGn4mJcjn6WM+LHQrGjDGc5AI0FY9tF/W7ODy2aiuCkryOwIAKh0VaK94+jlKGVCGdrZ28X125Z059wd/EO0yWgO7mljDMHMtUbVVpZDEpxJL0zSUN+Ro7Bu3pf4/advMWzyLRG9xitLmPefZ7D3998wbPLNOOOSS+M+rqyCNuh9/kXY/PN8nDH6UmQVxLbMMdeWi1eGv4JdtbviGlimBaMJuHkRUFvSIBgLBWbHBF70vSU643G7sPrzOSjoehK6nnkWzBZW7SGlLQrc0oHBGAwmWIfaI0kMM6frZZ+hZZAVYsVxgdt+YT/65eu4BDPRh5MvUnsEzQo13i7sdrJqY3Bk5+CkswZj8+KFGHTFtbBYbU0+X3aJ+Pq5J1C2YxtG3nY3eg+P/97BkLMvn4ityxZh1ScfYPTfHoj5fU7LOw2n5cXWYy/tZbQJ/iEkxaz58hP89n2wkrfFasVJZw1GjyHnod2pveKy5JtEjr7bzQj4/WoPgaS4Rnu5AfAFfKh0VeqzoiQhcVaxqwgmlkXrdh1UHUe/UWPhcbuwZWnTja9ddYfx2RMPoXznnxh9z/0JDdoAgG+VhTNGXYoda1agcs+uhB6LEJI+Du4vw4Yf5qHnuSNwxSNPo/uAc7BjzUp89sRDePOum7Dyk/dRU1ai9jDTBgVuTfjx//6Nd6ZPVXsYJMXl8/kAjg/cKl2V+u3hRkicle8uQn7nbjAYjaqOo7DbySjsfjI2zp8H5QQVbZ0Hq/Hp/3sQB0tLMO4fM3Hy2UOSMrYzx44H58jAio/fS8rxCCGpb9kHb8FkMWPINVPQoVcfXHT73zDtjQ8w6q770LpdB6yd+wXenT4Ncx76OzbO/xauusNqDzmlUeDWBDPHQRZj641DSKSsJiuy2CyUi+VHPR5qBUAZN5Lu/D4vDvy1W9X9bQ31GzUOtRXl2LNx/XFfq62swKePPQDhYDXGP/Q4upyevAp2rI3HwEuvwL5NG1G85Y+kHZcQkpr+2rgeezasw1mXXw2+VVb4cTPL4dTBw3D5jMdx66x3ce51N8Hv82HxO6/j9amT8fXzT6Dol5XweTwqjj410R63JrA2HrJLhKIotFGbJNRxTbgBlDpLAQBtecq4kfRWXbwPfq9X1f1tDXUfMAj27NbY8OM8dD1jQPjx6pJ9+OKfj8Dv9eKKR55GQdfkVzg9beQl2PDDPKz46F1c88//0LWLEBITv8+LJe+/hazCNuh38ZgTPs+elY3+oy9D/9GXoap4L7YtX4ztK5diz29rwfI8Tj5rCE4deh7antyDzkdxQBm3JrC8HQG/Hz5PCjXUJJpUwBccn3ET98PAGPTbw42QOCkPFybRRsbNaDLhtAtHo3jz76gu3gsguAfv0//3IADgqv/3rCpBGwCYLBYMuuIaVOzeiZ2/JqHxPSEkJW2c/x0O7S/FsMm3wGgyR/Sa3A6dcO6kG3Hra+/g8oefRJd+A7Bt5RJ8+tgDePueW7Dqszk4VLE/wSNPbRS4NYG18QBAyyVJwhXwBagUK496bL+wH3m2PJiNkZ0wCUlVFbuKYMtsBUdOrtpDCetz/oUwWVhs+HEeSrZtxudPPQzWZsPEx59HTvuOqo6tx7nD0bpdB6z85AMqsEUIiZpYewhrvvgYnU87A136Rb/c22AwolOf0zHqznsx7Y0PcdHtf0dmXgF++eoT/O+eW/HRI/fhj4U/wC04EzD6yOnx/EhLJZvA2oKlnmWXCHs2NSMliVPIF8LpdULwCLBb7ACCPdza8LS/jZCK3UUo6NpdU8tsrI4M9BhyHrYu/xnbVyxFRl4+Jsx8Eo7sOPbgjJHBYMTgiZPxzQtPYcvShehzvvbbPRBCtGPVpx/A55ExbEpk/SqbYuGs6Hnu+eh57vlw1lRj+8ql2LZ8MRa99RqWvPsGuvQbgFOHnocup/ePOLN3rEDAD1kU4XY6IQl1kAQBbmcdJMEZfiz4txNuwQnJ6YRbqEN+566Y+PjzLf5/TCYK3JrA8sEbaIkybiTBGvZy62bpBiCYceuf31/NYRGiOtnlQk1ZCU4elJzKjNHoN2osNi3+Cfmdu2L8jMdhy8hUe0hhXfsPROFJp2DN5x/h1MHDYGb12+uSEJI8lXt2YfOShThj1Dhkt2kX1/d2tM7BgHETcObYy3Fg7x5sX7EY21cuw861q8HZHTh50FD0GHIe7NnZwUCrPsCSjgq66o4KviRBgCQKgKI0ekyGMYCz28E5MmC1O+DIbo28jp3B2R3Ibhvf/79koMCtCeGlki5B5ZGQVBfq5VYulqNbVjd4A17q4UYIgMo9OwFF0UxhkoZat+uAyc+9glb5hTBz2gqMGIbB0Kuvx6ePP4iN87/DgHET1B6SKtzOOuxe/yu6DxwUvqYTQhqnKAoWv/sGbBmZOHvC1Qk7DsMwyO/cFfmdu2LotTdi36aN2Lp8MbYuWYg/Fnx/wteZOSusDgc4uwNWRwYy8vLr/+2A1e4IB2dc6Dn2DLA2W0o1CafArQksHwrcXCqPhKS6cMbNFawsWSFWIKAEqIdbGnPVHcbOX1ehS78BcLRWf/mdWkKFSfJVKvbRnNyOndUewgm169ELnU/vj7XffI4+518Ezm5Xe0hJU1d1AOu//xqbFy+AT5YR8PvRZwQtGSWkKX+uXo79O7Zh5G13J22iw2A0ovPp/dH59P6QXS7s+e1XeD2e+mAsA5wjGKRxdnvMSylTCQVuTaDiJCRZcqw5MDKmiCAfAAAgAElEQVRGlAvBypKhHm4UuKWf2opyrP9+LrYuXQSfR8bZEw5h0BXXqj0s1VTsKkJWYRtY7Q61h6JLQ66egvcfuBtr532Boddcr/ZwEq6qeC/WzfsSf65aBoZhcPKgodi+Ygnczjq1h0aIpnklCcs//B/yOndFz2HnqzIG1mbDqUPOU+XYekGBWxPCGTeRlkqSxDIZTMi15aLSFawsSc2300/5rh1YP+8r7Fy7BgajAacOOQ871qyEJKT3+adi1w6079lH7WHoVm7Hzjh18DBs/GEeTr9otCaKp8Sboigo274Va+d9gb82roeZ5XD6RWNwxiXjkJGTh52/rILsoglYQpqy9pvPIRysweh7HoDBYFR7OOQEKHBrgslsgdFkohM+SYpCvjDcy61MKIOBMSCfz1d5VCSRlEAAezauw/pvv0bp9i1gbTzOHDsep188FvasbJRs3ZTWE0fOg9UQDh1EgUb6t+nVOVdeix2rV2DNFx9j5K13qT2cuFECAez67Ves++YLlO/cAasjA4OuvBanXTj6qAwty/O0coaQJhw+UIl1336FU845F21P6aH2cEgTKHBrAsMwYHk7BW4kKQpsBdhSswVAMOOWb8uH2UDruVORz+vF9hVLsP67r3GwrASO1rkYNvlm9B4+EharLfw81maHlMbnn4pw423tFSbRk8y8AvS94GL8vuB79B99WdwrxSWb3+fFthVLsH7eVzi4vxQZufkYfuNU9Bo2otHqmayNT+vPESHNWfbh22AMBgy99ga1h0KaQYFbM1gbzdSR5CiwF2BR8SIElADKhDLa35aCJEHAHwt/wMb530KsPYTcTl0w6q77cNJZg2E0HX86TvdMQcWuIhiMJk0XANGLs8ZfhS1LF2HVJx9gzPQZag8nJh63C5sWzcdv38+FcOggcjt2xqi7/4GTzxoMg/HES7uCn6P0zVwT0pTiLZuw89fVOOfKSWldCEsvKHBrBmuzUcaNJEWBrQDegBcHpYMoE8owsHCg2kMicVJXdQC/fT8XmxcvgFeW0LHP6bj4jnvRoXffJptKszYetZXlSRyptlTsLkJux84wWSxqD0X3bJmt0H/0pVjzxceo2FWkq+WnYu0hbJz/LX5f8D1kUUT7nn1w4dR70LFvv4iasrO8HZLgTMJICdGXgN+PJe+9gYzcfJwx5jK1h0MiQIFbM1jentYz3iR5Qr3cSpwlOOA6QBm3FFD5126s//Yr7FizAgzD4JRBQ3HG6MuQ16lLRK9P54xbIOBHxe6dOHXIcLWHkjLOuOQy/P7T91jx8buYMPOfEQU9aqqtKMf6777ClqWL4Pf50P3Ms3HmuMujXjrL2ngcrqxI0CgJ0a9Ni+ajungvxkyfAbOFVXs4JAIUuDWDtfFwVlepPQySBkK93H4/8DsUKFRRUqcURcHePzZg/bdfoXjLH7BYreg3ahz6XTwWGTm5Ub0Xx/OQXem5xOvQ/jJ43G4U6igzpHWszYazxl+FJe+9iX2bNqJT335qD6lRlXt2Ye28L7Hzl1UwGA3oMXQ4+o8ZH/PevODnKD0nQAg5EbfgxKrPPkT7nn3QfcAgtYdDIkSBWzNYOuGTJAll3H6r/A0A9XDTG7/Piz9XLcf6775GdfFe2LOyMeSa69H3gotjbmTK2uzwuN0I+P1N7uFJRaHG23pa0qcHfS4Yhd9+mIcVH7+Hjr1PA2MwqD0kAMEJj+LNf2DtvC9QvPl3WKw29B9zGfqNGgd7VnaL3pu18ZAEAYqiaD7LSEiyrP5sDmRRxHlTbqHPhY5Q4NYMKk5CkiWTzQRn5LDhwAYA1MNNL2SXiE0//4QNP3wD4WANctp3xEW3/x2nnDMURlPLqoKGe0m6RFgdGfEYrm5U7CqCxWpDdiFNYMSTyWzGOVdeix9f/Q92/LISpwwaqup4AgE/dv66GuvmfYnKPbvAt8pq8YTHsVjejoDfB59HbrTqJCHpprp4L/5Y+AP6XHAxFX/SGQrcmsHaePi8Hvg8HtogTxKKYRgU8AXYW7cXRsaIfBv1cNMyZ001Nvw4D5sWzYfH7UL7nn0w8ta70Om0M+I2e8nxdgCALKZh4La7CAVdu2smI5RKThl8LtbN+xKrPv0A3QcMarSiaaJ5ZQnbli/G+m+/Rm1lObIK2+CCW+9EjyHD436tDQWAsihS4EbSnqIoWPLeG2CtNpxz5bVqD4dEiQK3ZjSc8abAjSRaKHAr4AtgMtDHU4sCfj8Wvvkqti3/GUpAwUlnnYP+Y8ajoGv3uB+r4fknnXg9Mqr2/YX+Y8arPZSUZDAYMfjqKZj7/BPYvHgBThs5KmnHrirei02LfsT2FUshu0QUdO2OMdfOQLczz4LBkJjlwJy9fgLEJcKe3TohxyCkoZJtm1FbWY5ewy7Q3DLEXevWoHjLJgy/4ba0mxBMBXRn2AwuNFPncoFvlaXyaEiqC+1zS8YyyS+ffhQ9hg7HqYOHJfxYqaRk62ZsWbIAPc89H2dPuBqZeQUJO1YoUyClWQ+qqr17EPD7qfF2AnXpdybantIDv3z5MXoOHQ4zl7hMlNcjo2jNSvyx6EeUF/0Jo8mE7gPPQd8RF6PtqT0TfmN75HOUXhMgRD3rv/sae35bi7I/t+GCW+5o8bL5ePF5PFj2wdvIad8RfS9I3oQNiR8K3JphCQdu6XXjRNQRqizZhk9s4Bbw+7H3jw3IzC+kwC1KkhjsB9V/zPiEBm1AcG8OkH4ZtwoqTJJwDMNgyNXX45PH7seGH+dh4GVXxv0Y1SX7sGnRfGxbsRiyKCKrsC3Ove4m9Bg6HLaMzLgf70SOZK7pOk6SQxIEWKxWbF26CIcPVGDs9Ic0kd1a/93XOHygEhNmPpV2Ba9SBQVuzQif8GmmjiRBKOOW6IqSoQyOnGaZnHiQhOD3LHRuSKSGe3PSSfmuIthb57S4miBpWttTeqDLGQOw9psv0GfERXG5sfR6ZOz8ZRX+WDQf+3dsg8FoQveBg9B3xEVo16O3KsvGWNuRvaKEJIMsCujY+3R0HzgIP81+GR89fC8ue/CxmFtaxIPzYDV+nfsZup15Njr2Pk21cZCWocCtGUeWStIJnyRePh8sSNLWkdjALfT7nG5L8OIh9L0LFQ5JJC48cZReP6eK3UUo7ErZtmQYMnEy3rv/Lvw693MMu+6mmN+nprQEmxb9iG3LF0MSBWQVtsHQSTei57nnJzW71hiOJmBJksmiAJbncergYcjMy8c3L/wTH828F2P+PkO1oGnFnHehBAIYNjn2zzlRHwVuzUjXpUpEHX1z++Lizhfj7MKzE3ocWaCMW6wkUYDBaILJwib8WGbOCoYxpNX5x+2sQ21FOXoPv1DtoaSFnA6d0HPocPz+03dRN4n3eTzY+Wswu1b251YYjCZ0G3A2+o64CO179tFMUQYLTcCSJJNcYvj+sc1Jp+Kap/6Nuc8/gS+ffhQjbrodfUZclNTxlO3Yju0rl2LgZVclfIk/SSwK3JpBSyVJMvFmHs8PfT7hx5HCGTf6vY6WLArg7Pak3JQyDAOW59Pq51SxeycAoJD2tyXNoCuuxZ+rlmHNFx/hwqn3NPv8mrISbP55PrYuWwxJcKJVfiGGXHM9eg0bAVtmqySMODomsxkmC0srDEhS+H1e+GQ5vGILADLz8jHxiX/h+5efw8I3/w8H95dg6KQbE1ZJtSElEMCSd1+HPSsbAy6dkPDjkcSiwK0ZZpYDY0ivGW+S+kITEZRxi54kinFrDBwJlufT6vxTsasIYBjkd+mm9lDSRkZuHvqOvAQbf/wW/UdfhtbtOhz3HJ/Xi51rV2PToh9Rum0LDEYjuvU/C31GXIwOvfpovt9eun2OiHpC11fWfvRyetZmw6X3P4plH7yN377/BofK9+OSu/8Bi9WW0PFsWbYIlXt2YdSd98LCWRN6LJJ4FLg1g2EYsLb0mvEmqU9uUJxEURTNLGnSA1kUkrK/LYS18WkVYFfsLkLrtu0TfjNDjjbwsiuxZckCrPzkfYy7b2b48YP7y7Dp5/nYuuxnSM46ZOblY/DVU9Br2AhdtcgJfo7oOk4SL5TZ5RqZ4DMYjTjv+luR1aYdFr8zGx8/ej8uu/9RZOTmJWQsskvEyo/fR+FJp+AUqiCdEmIO3BiGeQ3Aj4qifMswzNsAegD4XlGUp+q/ftxjesXyPDw0U0dSSOjC4vf54PPIMLOJ6+GUamRRAJfEss5cGi2VVBQF5Tt3oMsZA9QeStqxZWSi/5jxWP3ZHJRu2wKh9iA2LZqPkq2bYDAa0bX/QPQ5/yJ07H2a5rNrjaGMG0mWE2XcGjpt5Ci0KijEdy8+izkPT8el/3gEhd3j37fyl68+havuMC574DGaoE0RMZ19GYYZAqCgPmgbD8CoKMrZALowDNO9scfiOOakY210wieppWEGh2ahoyOJQpKXStrTJuNWV1UJt7OO9rep5IxLLoUtsxU+ffxBfP/y8zh8oBKDJ07GLa++g7HTH0Knvv10GbQBwexHunyOiLpCE6OhNhQn0qnP6bj6yRdg5jh8+viD+HP18riO4+D+Mmz4YR56DRuBgq66vg0nDUSdcWMYxgzgTQA/MAwzDsAwAJ/Vf3kBgMEATm/ksZ0tHaxaaKkkSTUNJyIkUYA9u7WKo9EXWRSTvFTSnjYTR+Xhxtvxn3kmzbNwVoy4+XYU/bIKPYYOR6c+p+s2UDsWy9tRW1mu9jBIGghNEERynWjdrj2ueerfmPfvp/H9y8/j0P4ynHX5xLhkx5a+/yZMFjMGT5zc4vci2hHLGXkygG0AngcwAMAdAMrqv3YQQD4AvpHHjsMwzK0Mw6xnGGZ9VVVVDENJjnTbY0JSX6iJNEAZt2goihLMuCWh+XYIy6fP3pyKXUUwmS3Iad9R7aGkre4DBuGSu/+BzqedkTJBG0ATsCR5Qr9nkV4nbBmZmDDzKfQ893ys/nwOfvjvC/B5PC0aw56N6/DXxvU46/KrdbUXlTQvlrPy6QDeUBSlAsCHAJYDCJWpsde/p9DIY8dRFOUNRVH6K4rSPzc38t4xyUZr40mqkV0iDMZgGWIqkR05ryxBCQSSmnHjbDy8sgS/z5e0Y6qlYncR8jp3hdFEdbNIfIUmQBRFUXsoJMVFk3ELMZnNuHDa3zD46in4c9UyfPbkQxBrD8V0fL/Pi6XvvYWswjbod/GYmN6DaFcsgdsuAF3q/90fQCcEl0ICQF8AewH81shjusXxPGSXS+1hEBI3kijAUd9olyYlIhfKVCY74wak/s/J7/Ohcs9uFND+NpIArI1HwB8sxkRIIkmiAKPZDJPFEtXrGIbBwEuvwNjpD6Fq71/4aOa9qC7eG/XxN/74LQ6Vl2HY5FtgNJmjfj3RtlgCt7cBnMcwzHIAtyO4x+06hmH+A+BKAN8DmNvIY7rF2uzwSm4E/H61h0JIXMiiiMzc4ArmhssmSdNimUltKbb+WKkeuNWUFsPnkSlwIwkR+szSCgOSaLKrZfuguw8chImPP4eAz4ePH/0H9mxcF/FrxdpDWPPlJ+h82hno0u/MmMdAtCvqwE1RFKeiKFcoijJUUZSzFUXZh2Dw9guA8xRFOawoSt2xj8Vz0MnG2oL9hFL9xomkD9klIqM+cKP9m5ELl3lOch+3hsdOVRX1hUkKqTAJSYBw5jrFP0dEfbLQ8srD+V264Zqn/4NW+W0w97knseHHeREt8135yQfweWQMm3JLi45PtCsuO48VRTmkKMpn9fveTviYXoVnvOmET1KAoiiQBAHWjAxYrFbILgrcIiWpknFLjxvO8l1F4BwZyMxrtJYVIS2SLhMgRH2SS2yyh1ukHNk5mPj4c+jafwCWvPsGfn77tSb3Olfu2YUtSxfi9IvGILtNuxYfn2hT6pSMSqDwCZ8ybiQF+DwyAn4fON4O1maHJNDvdaRC54BkZty48PkntQPsit1FKOzanZrEkoRIl72iRH2yKITP2y1l5jiMnf4Qzhw3AX8s/BFfP/d4o8t9FUXB4ndeh9WRgbMnXB2XYxNtosAtAnTCJ6nkSHNQvr7wTmoHBPGkTnGS1N+b45HcqCkppv1tJGG48MqZ1P0cEW2QRTGuk3uMwYCh11yPC6f9DSVbN+PjmfehtuLonoR/rlqG/UXbMXji5BYv0yTaRoFbBGiJBUklcoMeMyxvT+mAIN5CQW5o32sypMNSyco9u6AoAQrcSMKEJ0BoApYkWLDXZ/xXZfQaNgJXzHwKrrrDmDPzXpRu2wIA8EoSls95B3mdu6LXeSPiflyiLRS4RSAUuEmUmSApoOE+LZa3Q6aqkhGTRAEWqw0GgzFpxzSzHAxGY0pn/EOFSQq6UuBGEiNcZCyFJ0CI+hRFgSy2rKpkU9r16IVr/vlvWB0Z+Pypmdi67Ges/eZzCAdrMPz625J6bSLqoC6nEQjNeHuolxtJAQ0zbhxvx4EUDgjiTRZFcHHYdB4NhmHA2nhIKXzDWbGrCJn5BbBlZKo9FJKijCYzTCyb0hMgRH0etxuKEkjocvqsgja45skX8O2Lz2D+ay+CMRhwyjnnou0pPRJ2TKIdlHGLAGu1AQyT0jdOJH3IR2XceNrzEQVJbHmZ51ik+s+pfHcRZdtIwnG21P4cEfWFltMnuvIwZ7dj/IzH0feCUbBlZGLotTck9HhEOyhwiwBjMMDCUdl0khqkBr3ION4Oj5uay0dKFoWktgIIYW32lM0UiLWH4KyuQiHtbyMJxvJ2WipJEiqZBayMJhNG3Hw7bpv9PhytcxJ+PKINFLhFKDjjTSd8on9HCmzwVDE1SvGuFhapVD7/lIf2t1HjbZJgrI2n4iQkoWQVen1SC5X0QoFbhDgbTze3JCXIogAzy8FoMoUvLlRZMjLBamHJXyqZyuefil1FYAwG5HXuovZQSIpL5QkQog2hiQEqyU8ShQK3CLF86i5VIulFEkWw9QU22HBvI/rdjkQiq4U1JZX3uFXsLkJuh84wW1i1h0JSHGujvpUksUJVmpNdxIqkDwrcIkQzdSRVyKIArn42MJQ9ooxb8/w+H7yypErGjeXtKbnESwkEULGrCAXduqs9FJIGaI8bSTQ5nHGjwI0kBgVuEWKtNsq4kZQQ3KcVDD44yrhFLPT5V6c4CQ+fLMPv8yb92Il0qGI/ZJdIjbdJUnB8cMmxoihqD4WkKEkUAIYJ9w0kJN4ocIsQzdSRVBHcpxVaKllfnIQybs06Ui1MnaWSQOoF2KHG24VUmIQkAWvjEfD74ZNltYdCGlACARzYuwdKIKD2UFpMFkWwVhsYA91ek8Sg36wIsTwP2e1KiRMLSW+ySwwvlaTiJJFTo1pYyJGfU2oFbuW7imDmrMhu207toZA0EF4aTvvcNEFRFOxcuxrvP3A3Pnjgbuz+ba3aQ2qxhhOjhCSCSe0B6AVr4wFFgUdyU7UgomuSIISLk5gsLAxGE2XcIhD6HqmacUuxG86K3UUo6NINBoNR7aGQNBDadySLIhzZ1PdKLYqiYM+GdVj92Rwc2LsbGbn5AABnTZXKI2s5tXp9kvRBgVuEQsGaLIoUuBHdCgT88Lhd4RsYhmHA2e2UcYuAFM64qVCcxJZ6exF9Xi+q9u5Bv1Hj1B4KSRNUjEldiqJg7x8bsPqzD1Gxeyda5Rfi4jum46SzBuPl68aHl6PrmdRgDzkhiUCBW4QanvAzcvNUHg0hsfG43ACOXu5H+zcjE64WpspSydRrlF61bw/8Ph8VJiFJw9lSc6+o1imKguLNf2DV5x+ivOhPZOTmY+TUu9FjyHAYTcHbUIvVBklwqjzSlpNFAdltaOk3SRwK3CIUyrJ5XC6VR0JI7KTwcr8jM4KcjacZ6AgcKU6iRsYt9W44qTAJSTY2BSdAtK5k22as/mwOSrdvgaN1Li645U70HHY+jCbzUc/j7PaUCdwo40YSiQK3CIWLA9AJn+hYYwU2WLsdkrNOrSHphuwSYTSbVWkUnYpLvCp2FYHPyoY9u7XaQyFpgg23P0mdz5FWlf65FWs+n4PiLZtgz8rG8BunovfwC2Eymxt9Psc7UuL8JrlEKk5CEooCtwhZ6nty0Amf6FljGTfWxuNwZblaQ9INSRRU298aLiKTQhNH5bt3oqDrSWAYRu2hkDSRiplrrdlf9CdWfz4H+zZthC2zFc6bcgt6j7io2QmvYMZN3/dXfp8XPlkOL8klJBEocItQ+ISfQjdOJP2E92k1uLBwvP4vmMkgC+pVC2MYJtiSJEVuOCVBwKH9peg5dLjaQyFpxGgywcxytHImASp278Tqz+fgr43rYXVk4NxJN6LvyFEws1xEr+fsDlQX703sIBMsdH4OVW0mJBEocIsQzdSRVBAK0LgGFxbObofsEqEoCmU/miC5RFUvyBzPp8zEUcWenQCAgq5UmIQkVypNgGjBgb17sPrzOdi9/ldwdgeGXHM9TrvwElg4a1TvkwrVjcOVhynjRhKIArcIhWbqUuXGiaSnIxm3BnvcbDwCfj+8shT1xTadyKIAW0amasdnU6iITKgwSUG37iqPhKQb1sanXD9ENVQV78Wazz/CzrWrwfI8zrlyEk6/eCzY+m0l0eLsDkiCU9cTiJRxI8lAgVsU2BSa8SbpSRYFMIwBFuuRAC20kVoSBArcmiCLIrIK26p2/GDbhtS44azYXYTsNu2oJyZJOmp/0jI1pSVY/cVHKFqzAharDWdPuBr9Ro1r8TJyzu4ITiBKblissQV/agvvIbdR4EYShwK3KLA2WmJB9C3UHLThjObRPcJyVRqZ9kmioGq1MJa3w1ldpdrx40VRFJTv3IFOffupPRSShjieh1h7SO1h6M7B/WX45cuPsX3VMphZDgMvuwpnjL4UVrsjLu8frtwtCroN3Bqr2kxIvFHgFgVaYhE558FqsDaeMjgaI4vHF9gIl8imAiUnpCgKZFFU9YLM2VIj4++sqYLrcC013iaqYG08DpaVqj0M3aitKMcvX32CbcuXwGgx48wx49F/zPi4LxsP7buWBAEZOXlxfe9kkUJLJamPG0kgCtyiwPI8XIdr1R6GLnzy6AM46axzcO6kG9UeCmmgseag1KOweR63G4oSUPWCnCpFFcKNt6kwCVEBy/N0rotQ+c4d+OSx+2EwGNFv1FicOfZy8K2yEnIsrj5zp+cm3JRxI8lAgVsUWBuPQ/vL1B6G5imBAJzVVSmxrCvVNNYclJrSNk8LF2TWxsPn9cDn8cBksag2jpYq31UEo8mE3E6d1R4KSUOsLbhXVM9FMJKlbMc2BPx+3PCf2WhVUJjQY6VC4CaJAoxms67Pz0T7DGoPQE9YG83URUJ2uaAoAbh1fAJOVbIgHFeqmGtQnIQ0TtJC4BYKsHV+DqrYXYS8Tl1hNJnVHgpJQyzPQwkE4JUltYeieZIggDEYkJlfkPBjNVwqqVeyS93l9CQ9UOAWheBSpeBMHTkxt1AHQN8zZ6lKbqQXmcVmrf+afi+YiRbKuKm9VBLQd+AWCPhRuXsX7W8jqqGerJGThDpwvD0pmclQxk3PE76yIFClXJJwFLhFgbUFZ+p8sqz2UDQtFLBR4KY9knj8hcVgMKZUj7BECGXa1awqyaXADWdNaQm8skSBG1FNuIoune+a5RYEcI6MpBzLbGFhNJt1fd8gNTIxSki8UeAWhSNFHOiE3xTJSYGbFvk8Hvi93kaXclBvo6aFKm5yWsi46fiGM1yYhAI3opJQjy3a9tA8yVkXt3L/keDsDl2f32Tx+K0IhMQbBW5ROHLjRCf8poSWOnjcbvh9PpVHQ0LCzUEbDdwo49YUWQMZt/ANp45/TjWlxTBZWLQqaKP2UEiaout45NyCM7z3LBk43q7vPW7i8cW/CIk3CtyiwNY3haQTftMaZtoo66YdchM9ZjjKuDVJEgWAYcLnADWkwh43t7MO1owMquZHVJMKn6NkkQQnrElaKgkEM256vmeQRIECN5JwFLhFIVWquiWa29kwcNPv7FmqaaoyImvjdb1EJdFkUQRrs4ExqHfKDN1wSjoOsCXBCas9eTeChBwrtMeXrk3Nk5xJzrjpOHBTFAWySFUlSeJR4BYFmqmLDGXctClUNbKxqlec3a7rJXiJJomC6hfk0OZ9PZ9/3M46cI7k7Zkh5FjhqpK0V71JPq8XXlkCl8SJFs5uh1un1yGP2w1FCahaeZikBwrcokBlhCPTMFjTc2nfVBP6vW1sBjWYcaPf6xORRSG8x0xNes+MBjNuFLgR9RhNJphZjs53zQhdx7lkFifh7bqd7A1NBKg9wUdSHwVuUTgyU0cn/KZIghPWjMzwv4k2hIuTNJZx4+3wyhIVkzkBSRTB2dWfSdV79c9klhcn5ERYnqfreDNC125rEjPknN0BnyzD5/Um7ZjxElp6Sxk3kmgUuEXBZLEE+4zoeMY7GdxOJ7Lqq8ZJzjqVR0NCjhQnaSTjZqf9m03RSsaNs+n3hlMJBCALAqzU54iojFYYNC/U1iepGbf6Y+lxVYHcxB5yQuKJArcosTYeHpdL7WFomiQ6kZGbB8ZgoCBXQyRRgMnCwmQ2H/c1jjbsN0nWSLUwltfvDafkEqEogaTumSGkMZzdTnvcmuEWgpOuyQ3c6lue6HClTqgvYGMrWgiJJwrcosTydmrc2QzJGSwhrOcKUako2GOm8YtKOONGgXajpCa+d8nE2njdnn9C2fdkLr0ipDGsjdd1ddZkCE3iJXupJKDPvfFy/fcrmVU4SXqiwC1KrM1GN7dNCPj9kF0iOLsdVrvjqNYARF1yE5URQ8sA6Xf7eD6vFz6PrIklMMGMmz5/RqFzAVWVJGpjebtulxwni9uZ/IxbqHCRHld+yOGMm/rXCZLaKHCLEqvjPSbJEO4VZqeMm9bILuGEyzhCQQktbT1eKFDSRMZNxzec4WIHtFSSqIz2uDVPEoVwBc5k0fVSSVEAGAaszab2UEiKo8AtSsEbJ9rjdiLuBsuhOLtdlzNnqUoSxAcKL7EAACAASURBVBMu4+CoOMkJNdW4PNlYGw+/1wuvR1Z7KFELz+BTxo2ojKvfK6ooitpD0SzJWQfO7gDDMEk7ZmgfsR4DN1kUwVptYAx0W00Si37DosTpvI9Soknhdd4OWB0Z4Q3ORH1NZdxYKk5yQuH+dxoI3Dhev70kG54bCFETa+OhKAF4JbfaQ9EsSRCS/lllrTYwjEGX91iSRgpYkdRHgVuUqP9L06T6QM1qp4yb1gSLkzR+YTFZLDCZLbRUshGaWipp03PgVgeGMYQrmBKilnBmR4efo2RxC3VJD9wYgwGs3Q63Du8bmtpDTkg8UeAWpdBSJZ/Ho/ZQNKnhrDrHO+CV3PD79NdMM9UogQAklxjO2DSGJiUaFy7zrIGLcujGQI+lzN1OJ1i7nZYSEdWFJmHofHdikiCoUgHWarfrcqmkVioPk9RHV9AohWe86YTfqIb7WDhHsAgBZd3U55HcgKI0GXywvD1c0pgcES7zrIHALfTz02PGzS04w1XjCFHTkcx1fM93voMHEZCkuL6nWoJ73JJfSIjj9VnUjDJuJFkocIsSzdQ1TRIEMIwBrNWm6wpRqSYUPDc1I8hRj8JGyRpqrBr6+enx5yQ566gwCdGEI5nr+H2OAm43/hp3KfZeNRF+QX+fz4YURYFbcKrSk0yvWyxkUaCMG0kKCtyixOq4OEAySEIduPrlUKGy36EsHFFP6AaFa6LHjJ57hCWSJAowmS0wWSxqD0XXe9wo40a0IhGfo0OffgpfVRXknTtRdu90KD5f3N472XweGX6vF1ZH8jNuLG+HJOpvsldynXgPOSHxRIFblFhrYpZYpAp3g0pURzJu9L1S25GM24kvLBxvp+IkjZAEAawKM8+NSdQSr2SQBKcqN4KEHCucuY5T4BaQJNS8/TZsAwei4JGZEJctR+Vzz8flvdXgdgYDJ3Uybg7dLdn3+7zwyTIVXiJJYVJ7AHqj56VKydBwOVQogKOlkuoLFbNoaikHy1NT2sbILu3sXQhV/9TjUm3Jqc7SK0KOdWSvenwChNovvoS/qho5L/wb/MAB8Ozdh4PvvQdLp47IvvbauBwjmULXbKsae9zsDkguEYGAHwaDMenHj0XouqmVCT6S2ijjFqXQja+HmnA3ShKE8HKoUEUqNwVuqoukiTTH24NNaQOBZA1LF2TxxP3v1KDHANvn9cIrS6oUOyDkWAajEWbOGpfMdcDjQc2bb8La/wzYBpwJAMi7/x+wn3ceKv/5NIQVK1p8jGQLBW5qTLRY7XZAUSDr6B4rfH3V0HWCpC4K3KIU2iNES8oa17D3i5mzwmA0UsZNA8Izgk1m3OxQlAA8KVIVLV4kUdRUpoi18bo7/0j1+1zVKC9OSGNYno/LUsnDX30FX2UlcqZNA8MwAADGaETbF/4F9uSTUfa3v0MqKmrxcZIpHLipsLRZjyt1KONGkokCtyiZWBaMwaDLpUrJIDmd4ZszhmGCyx50dAJOVbJLBBgGrNV2wuccKbyjr6Ag0TSZcdPZ+ccdnsGnjBvRBs7W8sy14vGg+o03YO3bF/ygQUd9zcDzaD/rNRhsNpRMnQpfVVWLjpVMoT1uahQT0mPgFppIY5so/kVIvFDgFiWGYYL9rnS2VCkZwsuh+CMne87ugOTUzwk4VUmCANZma7L5cWgZpd6yOYkmi9qqFhY8/+jrZ0QZN6I18ZgAOTxvHnz7y5Fzx+3hbFtD5oICtJs1C/5DtSi5407d9Hg7slRSjcBNf0XN5Ai2IhASLxS4xYCz6W/GOxkaW17B2R26LO2bamSX2OxFJTRbqLegIJGUQACSSwSnof48rA7PP24VbwQJaQzbwoyb4vWievbr4Hr1Aj9kyAmfZ+3VE23/9TykzZux/8EZuthD7BacMLGsKi1QWB1OIEoRbEUgJF4ocIuBHpcqJUNjG5o5ux1uHc2cpargcr+mA7fwTKeOLpiJ5pHcgKJoKuMWbNugr/NPuEodtQMgGsHy9hZVlTz83ffwlpYi5/ZpjWbbGnKMGIG8++6Dc/58VL38SszHTJZgBVh1JlmsOlwqSRk3kkwUuMWgpTN1qUpyHl9C2GrPoKWSGhAssNH0bKCemzsnSmi5jpYuyKGqkoqiqD2UiKnZF4qQxnAt2PKg+P2omT0b7CmnwH7eeRG9JvvGG9DqiitQ8/rrqP16bkzHTRZJdKqyvw1okHHTUeAmiQKMZrMqGUqSfihwi4Eelyolg1tsPOOmpxNwqqKMW2zCm841tASGtfEI+H3weWS1hxIxSXDCZLbAzHJqD4UQAKGVM66Yli7W/fAjPPv2RZRtC2EYBgWPPgLb2Weh/NFHIa5dG/Vxk8WtYsbNaDLBYrXqa49bBFsRCIkXCtxiEJzx1s9JJVnCGbcGy6Gsjgx4ZQk+r1etYRHUB27NBB8WzgqGMdDvdgOhGXktXZRDY9FTZtTtrANHhUmIhrA2Pqb2J0oggOrZs8F27w7HiBFRvZYxm9HupZdgad8eZXfdDc/evVG9PlkkQb2MGwDdVaOWBW1VHiapjQK3GAQzbvppDpksJ9rj1vBrRB1SBJURGYMBrM2mu/1TiSSHM27aCdzCbRt0lPVX+0aQkGMd+RxFN1HlXLAAnt27kTNtapNVek/EmJmJ9rNnAQYDSm6bCn9tbdTvkWiSoF7GDQA4Xl+Bm+QSqYcbSRoK3GLA8jy8sgS/z6f2UDTFLThhMJpg5qzhx/TYkyXV+Lxe+DwyuAhmBFm7/krNJ5Lk0uAet/qfo54CbLfTqUozX0JOhLNFn7lWAgFUvzYLli5d4LjwwpiPbenQAe1e/T949+9H6V13Q/F4Yn6veFMUJRi4qZgh5+y8vpZKikJE11dC4oECtxiEizjoaMY7GSQh2Hy74Zr/cOBGBUpU46n/PY1kRpD2bx5NFjS4xy3GTIGaJGcdZdyIpoQ/R1EEbs6ff4ZcVIScqbeBMRpbdHxbv34ofPqfcK1bh/JHH9NMsSGP242A36/uUkneoau91lrr9UlSGwVuMaDArXGNlRAO/bebermpJnQBjGRGkOPtuprpTDTZJYJhDLA0yCKrLdxvT0c/J0kUaI8b0ZRw5jrC67iiKKieNQvmjh2QMWpUXMaQOWYMcu64A4fnzkXNG2/G5T1bShLqAKjbc1Fve9wkUaDAjSQNBW4xCH1APbTP7Shuoe64k70ee7KkmtCMciQZN46304REA1J9UZdY9rIkSqgZeKQ3nGoLL72ijBvREDZc5CeyCRBh6VLI27Yj57apYEymuI0j5847kHHJJah68UXUzf8pbu8bq3ALFBWXNgerUQuayUI2RVEUyCJVlSTJo527ER3hwntM9DPjnQySIByfcXPQUkm1hUvaN9MOAAguH6Lf6yMkoflqnMkWyxIvNXncLtWXXhFyrGiK/CiKgurXZsHcti0yx4yO6zgYhkHh0/+E9fTTsf+BB+DetCmu7x8ttzOUcVMvEOHsDgT8Pnjl6Cp+qsHjdkNRApq7TpDURYFbDPRY1S0ZJGcdrMcshzKzHAxGE2XcVBSaUY5kRpDl7bpagpdoWuzPYzSZYWJZ3Zx/ws23qTgJ0RDWagMQ2QSIuHIVpM2b0fq2W8GYzXEfi4Fl0e7V/4MpNxclt98Bb1lZ3I8RqdC12mpXM+Omn5U6sgYLWJHURoFbDMJ73HQy450sjWXcGIYJL3sg6ghVH4xkRpDj7fB5PfBpqMqZmiRRm/15OJt+eklK9TP4x07qEKImg9EIi9XabJEfRVFQ/eqrMBUWotWllyZsPKbsbLSfPQuKLKNk2u3wq3TNdDfS1ifZjrQR0v45TtJgASuS2ihwiwFl3I4XbLLtaXQfi9WRAXf9hmeSfEd6kUXQDiC074N+twFAs3sXWN6um4mjIzeClHEj2sLa7M221XD98gvcv/+O1rfcDMZiSex4unVDu5dfgrx7N8qmT4eiQsuhI/1Y1awqqZ/ALXSt1OJ1gqQmCtxiYOGsAMPQzW0DoRNsY/tYKOOmLkkUYDSbYbawzT43XPhCJ9mcRJNF7e1xA4JZf70UJwkvvaKMG9EYlm8+c1392iyY8vLQ6vLLkzImftAgFDz6KMTlK1D5zLNJOWZDktMJi9UG17Jl2P/AA9gzZizKpk9Hzf/egWvdOviFxJ93wksldVCN+sgecu1dJ0hqil9ppDTCGAxgbTbdzHgnQ3hDcyM3Z5w9A3UHKpI9JFJPdokRX1SirbSW6rTan4flebgOH1Z7GBEJ73Gj4iREY1gb3+R1XFy7Fq5165D/0EMwsM1PfMVL1lVXwrN3Lw6+8w4snToh+7pJCT+mXxAhLl+GmqVLYKyrQ+kdd8KQmQlr795w/f476n74MfhEhoGlaxdYe/UG16sXrL17gT3llLh+f3S1xy1UhVPFpaUkvVDgFiNWR3tMkiFcQphvPONW+Rd9r9QSzXK/8BIV+t2Gz+MJLv/VYuBm43GoXL0CBtEI94XS4PeRpDeW5+GsqT7h16tnzYIxJwetrrwiiaMKyrvvXniKi1H5zDOwdGgP+7nnxv0Y/sOH4Vy8BM6FCyGuXAnF44H7pA6wZmWi/dtvgR8wIFyMxVddDfeWLZC2bIW0eTOEFStweO7c4BuZTGBP6h4M5nr3grVXL7DdusVcyEVPe9xCK68iqdpMSDxQ4BYjPS1VSobQzVljy6H01kwz1UhRLPfTW6n5RAovgdFgwKGrPW5OJ1ieh8FoVHsohByFs/GoLt7X6NdcGzbCteYX5N1/Pwwcl+SRAYzRiLb/eh57J01C2d+no+PHH4E7+eQWv6+vuhrOnxfDuWABxF9/BXy+YOGViVchY+RIbPj6IzhsPOznnHPU60w5OXAMGwbHsGEAgkVbfBUVcG/eDGnzFkhbt6Bu/nzUfvZZcPwsC+7UU8NZOa53b1g6dYqoJ6bJwsJoNuvivkESBYBhwNpsag+FpAkK3GLE8jw14G7gSNPOYODm2rAR5vw8mNu2hdXugE+W4fN4YErw5m5yPFkUYcuIrDAEZdyOCAVGnAb3uHH1/fYURQHDMGoPp0mS4FS1tDghJ8Ly9hNWlayeNQvGrCxkTbwqyaM6wmCzof2sWdh7xZUomToNnT79BOa8vKjfx1teDufCRXAuWADXhg1AIABzxw5ofcP1cIwcCa5Xr/B5RP7wDWTmFTT7ngzDwFxYCHNhITJGjgQQDOa8xcVwb94CafNmuLduQe1XX+HQhx8G/394HlzPnuGsHNe7N8xt2x53DgtWo9bHhK8simCttogCUkLigQK3GLE2O+3bauBI004HpO3bse+662B0ONB+9qyj1qvbs1urOcy0JIsCsgrbRPRcyrgdoemMm42HEgjAK0vBYkka5nbWNbr3lRC1sTwP2eWCEggcdePt3rQJ4ooVyJ0+HQaVMynm/Hy0nz0Le6+dhNI77kTH99+Dwdr8Z95TXAznggWoW7AQUn1Tb7Z7d+RMmwbHyJFgT+re6KSP2+mMeT8qwzCwdOwIS8eOyBx9CQBA8fvh2bMnGMxt2Qz3lq049P4HOOj1AgCMrVoFs3J9+yJ78nUwZmYCCE4i6mGpZHBFi/auESR1UeAWI9Zmo6WSDbgFJ0wWFibGgJKHH4YxKwsGmw37rr8BuGsqAArc1CK5Ii+wEWruTBk3bTdWbRhgaz1wkwQnbBmZag+DkOOwNh5QFHgk91EFnKpnzYYxMxNZ11yj4uiO4Hr0QNt/v4DSO+7E/gceRNuXXjwuw6MoCjy7dqFuwQI4FyyEvGNH8LW9eiF3+nQ4LhgBtnPnJo+jBAKQRCGuFWAZoxFs9+5gu3cHxl8WPI7HA6loJ6QtW+DeshnSlq2onjUL4sqV6PDO/2Cw2YLVqHVwHZJFQZPXCJK6KHCLUbCMMAVuIZLgBGe3o+Z/70Deth1tX3kZtn79UHLbVFS9/ibQuSDcz4kkj6Io9ReWyJf7cbw9roV36hYuBGMwwHH++XF7z2SQNdxYNbQRXhYFOFrnqDyapkmCE9lt26s9DN1z//FHcN/QKaeoPZSUwYWr6B6pvCtt2wZhyRLk3nM3jHbtfPYdw4cj7/77ceC551D14kvIu3c6FEWBtHUbnAsWwLlwITx//QUwDKz9+iF/xoNwjBgBc9u2ER9DcomAojTa1ieeGIsF1l49Ye3VE1kILkV1LlqE0rvvQend96D9a6+CsztQV3UgoeOIB0kUNXmNIKmLArcYsTY7PJL7uCUW6UoSnGAtLKpffRWOCy8Mr3nv8N57cN4xDZAO4sCXX6Ldqb00vycnlXjrf0ej6THTXInsaNS8+y4OPPscGKsV3RYthKm1fjKukoYbq4b3Iuog6x9cehUcr6ekBK6165AxZjQMtN81Yu4tW7HvuslQ/H7k3HYrcqZNi7liHzmCbdC3MiM3uHesetYsGBwOZE1KfAn+aGVfPwWevXtR8+ab8JaVwv37H/Du3w8YjeAHDkD2lMlwnH8+TLm5Mb2/ms23HSNGoPCJx1E+8xHsf+hhcF3a4MBfe5I+jmjJooDsNu3UHgZJIxRxxIjjg0ssZDcVKAGCTTsNFZVgrFYUzHw4/LjRzqPjM88AAGp+/AGVT/0Tit+v1jDTTiz7tOKxREVRFFS99hoOPPsc+HPOgSLLqHnr7Ra9Z7JpOuOmk72Ifp8PHrcLVnsGFJ8Ppffcg/KHH8aeUZegbv58KIqi9hA1z3foEErvvgvGnNbIHH0Jql+bhb1XTYS8c6faQ9O9cOa6fgJE2rEDzoWLkF2/R1trGIZBwcyHwQ8eDOfCRWBPOgmFTz+N7itXoMP//oesiRNjDtqA4HUcaLwfazK0mjABudOno+677+Dfuk0nxUkir9pMSDxQ4BajUAZD6zdOySKUlcJYexj5Mx487sJhq9/XZho4EIfmzEHZ9HsRkGU1hpl2YqmM2NKMm6IoOPDCC6h+5b/IvPRStH99NjLHjMGhjz+Gr6oq5vdNNkkUYGJZGE3ay2yEAzeNZ9zCM/gOBw599DHkbdvR+tZbYbDZUPa3v2PfNdfC/fvvKo9SuxSfD2XTp8NfXYN2L7+CNs89h7b/fQXeigr8dfkE1PzvHZoIa4FjJ0CqZ8+GgeeRPfk6NYfVJMZsRvvXZ+OkdWvRfvYstBp/GUxZWXF5b3e456J6QWvrW25G9pQpCGzeAq8swVdfxESrotlDTkg8UOAWo3DgpvEbp2TwlJZBqj0Ea24eMseNO+7rwZtfE0xnnoG8+++H86efUHLLrfA7tT+bpnehG5KoMm587Bk3JRBAxRNP4ODb/0PWNVej8Ol/gjGZkHP7NCheL2reeium91WD7Iq8cXmyHZk40vbm/VDgZvErqHr5ZfCDByP3739D56+/QuFTT8JTWoK9E69G2fTp8JTqo6F4MlW9/DJca35BwWOPwdq7FwAg44IL0OXbeeCHDMGB559H8ZTr6XsXI67BBIi8axec839C1qRJMLZqpfLImsYYjQnpLReq4hjP4iTRYhgGeQ/cD0fPngCAyo8+Um0szfH7vPDJMrgotiIQ0lIUuMVILzPeiaYoCsoffRQeowHZQ4Y2un+NYRhwjgxIzjq0vvEGtPnX83Bt3Ih9k66Dt1L7m4/1LBSARROAsPbYipMoPh/KZ8xA7cefoPXNNyH/kUfC+z8tHTsic9w4HPr4E938zCVBiGpvYDLpJeMfahMiffc9FK8XBY/MBMMwYIxGtJowAd3mz0fO7dPgXLwEe0aNwoEXXqAJnXp1Py1AzZtvodXEq9Dq8vFHfc3UujXa/d9/UfjMM5C2b8dfY8ei9osvaOlplBoW+ame/ToYqxXZ109ReVTqkRq09VETYzAg/+pgRc/9L72Iup8WqDqeEwlPjNq1OcFHUhMFbjHSy41Toh3+ei7qflkDhWHAFxae8HkNe7JkjhmD9rNnwVtSgn1XXw15z1/JGm7aCU0sRJNxY212yO5gb6NIKR4Pyqbfi8PfzEPuPXcj9957jwvic6ZNhRIIoObNNyN+XzXJLjFcVENrjCYTzCyn+eIkoUqy3jVr0PrWW2Hp2PGorxt4Hrl3342u839ExqhRqHn7f9g98kIcnDMHisaXSCWSvGsXymfMgLVvX+Q/9FCjz2EYBq0uuxRd5n0DrndvlM98BKXTbtfVcmS1WWzBVhpiWSnqfvgBWVdPjNuyQz1yCwLAMJrYs2XNDGY9mZNPwv777oP4y68qj+h44YlRjU7wkdREgVuMQjfC6Zxx81VVofLZZ2E4rS+Apjc0c3bHURuN7eecgw7vv4+AJGHfNdfA/ccfCR9vOpJiKLDB8fZg4R1XZIV3ApKEkjvvhHPBAuTPeDBY8a6RzKulfXu0uuxS1H72GbwV2m9eL4nazbgB+mhJ4j50CABgyy9A61tuPuHzzAUFaPPsM+j0xedgu3dH5ZNPYc+4S+FcsiTtskh+pxOld94FxmpF21debrb6prltW3R453/If2gGxDVrsGfMWM1mKLTGYDDCYrXh8Nq1YCwWtL7hBrWHpCpJqANn42EwGNUeSjjrlzltKiydOqL0jjvg3rpV5VEdTc2Mm+L3Q1i+HCV33Ik9Y8dpMrAliUGBW4xYmw2A9veYJFLFE09CkSRkTAs22LbaM074XKvDcVwfN2uvnuj08UcwZGRg35Tr4Vy6NJHDTUuhJtKh39dIHFkG3Pzvtl8QUXLLrRBXrETBk08ge0rTy4xa3zYViqKg5o03Ih6PWmRR3T1uAbcblc88C9eGjY1+PVhERtvnn5rFPwMA2j3wAAws2+zzrT17osN776Lda68CgQBKp92O4htuhLR9e6KHqglKIID9D86Ap6QE7V56Eeb8/IhexxgMyJ48GZ2/+hLmdu1Qds89KLv/fvjr6hI8Yv1jWQ7Cvr3IuupKmHK03RMx0SRBUK2i5LFCgZsHCtq/9RYMmRkoueVWePbuVXdgDYSrNtuSd53wVVWhevbr2D3yQpTcehvcGzci4HKh+MYbUfPWW2k30ZWOKHCLUbhZp8ZnvBOlbv5PcC5ciJy77oQ/MxiwNbWs7NiMW4ilY0d0+mgO2C5dUHrHnaj98quEjTkdSaIAi9UW1QxquEeY0HRQ4K+tRfGNN8K1YQPa/OtfyLriimbf29KuLVqNH4/az78I9h/SsGCZZ3UCt4DbjZJpt+Pge++h9O674auuPu45LG+PKLhWi6e4GIfXrYMBQNaw8yJ+HcMwcAwfji7fzkP+zJmQ//wTf42/HPtnPARvZWXiBqwBNW+8CeHnn5H/wP2wnXlm1K9nu3ZFp48/Qs6dd6Lu+x+wZ8xYCKtWJWCkqcPocsFnMiL7xpvUHorq3M66Jidgkyl0PyEJTpjz89HhrbcBRUHxTTdrZp+0HMMe8lgogQDE1atRes/fsPO84ah66SWY27VD2//8G92XLkHnuXPhuOACHHjh3yi96y7aJ5ziKHCLkcFohJmzwuNOv8DNX1uLiiefBNejB1rfcEN4Q7PVceITfjBwa/wm05STgw7vvw9+4ECUP/wwqme/TrNGcSKLYtT7FcKBWxPZHF91NfZNuR7y9u1o98rLyBx9ScTvn3PbrVAAVL+u3aybEghAdrtUCdxCQZvr11+Rc8cdCDid2D/joeP2HHI8r9mJI0VRUPHkU/CYTeAyMhtdOtscxmxG9qRr0XXBT8i+4QbUffcddl90Mar++38IRLiMV0+EFStR9fLLyBg9GlnXxV6OnjGbkXvnHej0yScw8DxKbroZFU88mZLfs5bylpXBcKgWKCiAOT9P7eGoThKcmtnXy1ptYBhDeMKX7dIZ7d94A/5Dh1By883wHz6s8giPTNwnak+g7+BB1Lz9NnZffDGKb7wJrl9+QfakSejyww/o+N67yBg1CozFAqOdR9uXXkT+jAchLF2GvyZMgLRjR0LGRNRHgVsLsBq+cUqkymeehf/w4XCp91BA1lQlKs7ugM8jw+tpvH+b0c6j/exZyBg9GlUvvaS5Rt2e4mLUzp2Lw99+h7qfFsC5ZAmEVavgWrcO7j/+gLR9O+Rdu+ApLoa3ogK+gwfhFwQEPB5Vg1BJFKKeDWyuYqq3ogL7Jl0HT3Ex2s2eBcf550f1/uY2bZB1xQTUfvWVZsuYyy4XoChJXyoZcLlQMnUaXGvXos1zzyL3rjuR/+ADEFeswMF33zvquayN1+weW+dPCyCuWAHmpO6wZmS26L2MGRnIv/8f6PLjD7APOxfVr76K3RdehNovv9TUOaIlPCUlKLvvvmBD5ScejynQPZa1dy90/upLZE+ZjEMffYS/LhtPPfOOUf3mmzAFAuFVI+lOEpzgmpiATSbGYADL88GCKfWsvXuh3av/B8/evSiZdjsCbreKI0xMxk1RFIhr16Js+r3Yde4wHPjXCzDl5qLNv55Ht+XLkP/gA2C7dD7udQzDIHvKFHR8710oLjf2XjURtXPnxm1cyRRwRVccLd2Y1B6AnrFWm+aLA8SbsGIFDn/zDVpPmwrulFMANGja2cRMnbU+qJMEJ8zZje91YSwWtHn+OZhycnDw3Xfhq6lBm+eejWhvTCL4Dx9G3Y/zcXjePLg3bGjRezFmMxiL5cjfx/0xw2CxgDFbYOB5ZI4bC35o4+0VohFLxo1tYqmkp7gYxTfcCP/hw+jw1puwnXFGTONqfeutqP38C9S8PhuFTz4Z03skUnjvQhKrq4WDtvXr0ea5Z5E5ZgwAoNXEiRBXr8aBF1+E7cwzw/28WN6uyfOPXxBR+cwzYE89Ff6sVrDGIQgBAEu7dmj34otwTZ6MA88+h/KHZ+LgBx8i//5/gB80KC7HUEPA7UbpXXcDioJ2/30Fhij2ozbHwHHInzED9vOGY/9DM7D3mmvR+v+zd95xUlX333/fe6f32Z3tjY4x2GLNoybYERWMir0rIKiowYKgFBVQUBEFxa6RKGpQETUxiS1Rf2o0mqhREIHtbWZnd3q/zx93ZnaHXZbtu+J+4L7OndvO2VvOOZ9veZGuOQAAIABJREFUnTGdnNmzEfYQ9GRvR7SujpaNr2A84iBc0chgN2dIIOgdOho3UOYUu/rxGn/9awpXrqD6ht9TfcPvKX7oQQS1elDaF/L7kNRqVH3wLcWbm2l+7TWaX3qZyPbtiBYLtnPPxX72NLRjx3b5OoaDD2bkq69Q/fu51M67leCXX5E3/9ZBm0d1B4lQCNcTT+J6/HGsZ/yOgkWLBrtJQxLDxK0XUHxMht7Eqb8Q9/mpXbQIzejROGbNSm8P+XyodXok1e47z7S9uteLOWv3DuCCKJI37xZUubk0rFhBZVMTxWvXIA2Qw7QciSTJ6ev43nsPORpFM2Y0OXN/j/mYY0CUkKMR5EjmkkivR5P7o5nHRDs6LvOYRCCIHGkh+u23eN56C92ECTiuno1p4sQeE7hwwI8tL79b5+h2o3ELb9tGxWWXI0cilD7zDPoJv+xRm0CJImg75xzcGzYoYeJLSnp8rf7AQPkupJBJ2u7Betqp6X2CIFBw550ET/8d1TfOZeTGV5BMRnTJqJKyLPeJhqav4FyzhlhDA8WrHyC8/nFs+YV9en3DQQdRtuEFvH/+Mw333U/F5Vdg+u1vyb35JrSjR/dpXf0NJQ/mIsJbtlDy6Do0paX9Uo/xiMMZtWkT9cuW41r3KL4P/kHhPXejGzeuX+rrCuRolLjHgyo7e1Dqdz3xJLIsYzngAGq+GI7IF4/FiAQDQ8bHDXbvG2+ZNIm4203dkjuovX2hYv0jDrwBWTjQuwBWsiwT/PJLml98Ec+f/4IciaA/4AAKli3DcvIkRL2+R9dVORyUPvUkjatX43r8CULffkvRAw+gKS7qcVv7E7Is4/3732m4+x6i1dVoRoyg+YUNWE85BcMhhwx284YcholbL6AzGvG5mwa7GQOGxvvvJ1ZbR9nzf8wIUR3yetDvgVjpkoNBR51wR8i+/DJUOQ5qbp1P+YUXUfLYY/3mgyDLMqGvv6bltU143nqLeHMzUnY29vPPwzJlCrp99x3QibEcidC8aROudY9SNWs2ul/+UiFwxxzT7XYoIe27N7CodXoEUcyQdAa//ZbKK6eDSqL0uT/0yYQve/p0ml9+Gecj6yhctrTX1+tLDKTGLREIUDnzKgJffNGOtKUg2WwUrVxB+SWXUn/nnRTeczdagxFZThANBdHo+05L0xuEtmyh6bnnsE2bhv7AAwmu81LQD0IXQRCwTJ6M6bjjcK9fj3Pdo2yfMhXb2dPIueaaQSMD3YV7/R/xbN6MY861mH7zm36tSzKbKVy+DPPxx1F7+0J2nnkWOddfT9allyBI/Rv+PeZyEfr+e8JbthLesoXQ1q1Etm1DjkbRH3QQtmnTsEw6qU+1jZ0h2tBA80svYZ06habcvHTeysGY/A8VpIVVQ0rjZk770O8K+3nnEWtqwvnQGqSsLPJuvmmAWwdhX89SxsQ9Hlo2vU7zSy8R/uEHRKMR21lnYjv77LQlU28hqFTkzp2L/oADqJl3KzvPPJPCe1diOvroPrl+XyG8fTv1dy3F//HHaMeOVYTC++/H9tOmULtwESNfe3WPKVF+bhgmbr2A1mDEVV052M0YEAQ+/xz3889jv/giDAcdlLFP8aPaE3HrWqTCtrCedhqSPYvqOXMoP+88Sp54okPb7p4iWl1Ny+bNtLy2icjOnQhaLebjjsU6dSrG//f/Bs38QtBosE+bhu3002l5/XWc6x6lavbVaPf9BTmzZ2M67rguE7iw34/O1L2BRRCEjITpgX9/SeXMmYhmE2VPPYVmxIju/kkdQp2Xi/3cc2ha/0ccM9snZx5MpLSN/a1xS/j9Cmn7978pXLGi0yAvhkMPxTFrFs61azEe+f/SuYNCfv+QIG5yIkHdosVIViu5v79BEYh4PZ36vvYWolZL9hVXYD3jDJxr1uLesAHP65vJnjmTrEsuHtLmQYHPP6f+nnswHXMMjquuGrB6zccdh/7AA6lbvJiGlSvxvvcuhcuX94nWOxGJENm+XSFn329Jk7R4m6ioqtxctPuMx3TUkYhGIy2bXqd2/nzqly3DcuopCun/Zc+1+V1B01NPI8fjOGbOpPbrfyt5K4OBQU3/MdhIpesZKj5uoPS/zbW7jz7smD2beJObpqeeQpWdRfYVAxsZNBTwdzmHmyzLhP77X9wvvoTnrbeQQyF0EyaQf+cdWCdPRuwnIaH5+OMZuXEsVXOuo3LGTByzZ+OYPavfhTV7Qtznw7n2YZqeew5Rrydv/nzs55+HoFJoSf7iRVROn4Hr8cfJufrqQW3rUMMwcesFfgoJcPsCiVCI2gW3oS4qIvf669vtD3o9e8z9koo4mfKH6ypMRymJuitnzKD8/PMpeXQd+gMO6NY12iLu9eJ9+21aNr1O4F//ApQJcfaVV2A+6aQBM8nsCgS1GtuZZ2KdMoWWN97Eue4Rqq65Fu0+++CYPQvz8cd3KiGOx2JEQ8Ee5ZjRGpXAF/5PPqFy9tWoc3Ioffop1IV9a/aWfeWVuF98SdG63b28T6/dG/QkcXl3kfD7qZg5k+C/v6Rw5Qqsp+w5Mqdj1lX4P/2EusVLkO64HUiRzJx+a2dX0bxxI8GvvqJg+XIkm41IKEg8FutX4paCym4n//bbsF9wAQ333kvj/ffTvGED+UuWYDr6qH6vv7uI1jdQdf0NaIqKKFxxz4BrelTZ2RQ9+CAtmzZRf9dStk89nbx5t2CbNq1LQiFZlok1NBLemiRnW7YS/v57wjt2QCwGKAIo7dixmH7zG3Tjx6Edvw/a8eNQ2e0Z18qeOZPgF1/Q/PLLtLz6Gs0bXkS3777Yzp6G5dRTkfpYAxRzuXBv2ID11FPRlJai/VGJvjfYeRsHG6FkCHn9AHyvXcXuTCVTEASBvAXzibvdNKy8F8lmx3bmGQPWvrDfh2EPwZfiPj+eNzbjfvElwt99h2AwYD3tNGznnNMrd4PuQFNWxogNL1C3eAnOtWsJ/uc/FK5c0e5bHAjIiQQtr79Ow333EXe6sJ11JjnXX9/OSsJ09NFYTjkF17pHsZw8uU+F9j91DBO3XiAV1W2o+Zj0NZxr1xIpL6f0qSc7NGUJ+XxYHJ2bMfZE45ZCKlF3xZXTKb/0MopW3Y954sQuny9Ho/g++gjP66/jfedd5HAYzYgR5Fx/HZZTTxuydt8pCGo1tt+djvW0U/G8+SbOR9ZRPec6tOPG4Zg9G/OJJ3Q48UtpjXoS0l5nNOGvKKfyifVoysoofepJVDl9Tw5UOTnYzzuPpmefJXvmDLQjh0bn3N8atzRp+/Iriu5diWXy5C6dJ6hUFK1YwfbfnYH3mT+AxJBIwh1zu2m89z70hxyM9fSpQJuJ4ABK8LWjRlLy8Fr8n3xK3Z13Ujl9OrZp08i95eY+JwA9hRyJUH3ddSQCAcqefmrQhEWCIGA7/XSMhx1GzfwF1C1chPeddyi4807Uua39eSIcJrxtW9LM8XuFpG3ZQtztTh+jKihAN24cpmOPTZK08WjKytLS8z21w3DIIRgOOYS8+fNp2fwGzS+/TN3iJdTfswLLySdjm3YW+gMP7JNxtunpp5HDYbJnzgT2HEX354K0xm1IETcToYC/UzNWQRQpvHs58ZYWahcuRLLbMB977IC0L+z3Yy9oP3+QZZnQN9/Q/PKfaHnjDeRAAO0++5C/eFG/CCO6AlGvp+Du5eh/9Svq77qLHWeeSfEDD6Dff/8Ba0Pwm2+pv+sugl99he6A/Sl5+GH0++232+Pzbp2H75//pG7RIkr/8OxePc/uDoaJWy+gNRiREwmi4RAaXc+cSIc6gt98i+upp7GedeZuI7cFfd49dvYqjRZJre6yj9uu0JSVMeKF56mcMZOqq6+h4I47OpWsybJM6H//o2XTJjxvvkXc5UKy2RQN1ulT0e2330+uExBUKqxTp2I59VQ8b72F8+FHqL7+erRjxyoauJNOyhjcWgNsdF9rJAVDeLdtQztuHCWPP9avkrnsK6/AvWEDzkceoWjFin6rpzsI+30Iooi6H77ruM9P5cyZBL9KkraTT+7W+erCQgruvAP3LTfBuJIhkZKk4d57ifv9FCxalP6ugknflD1p4/sDxiMOZ+QrG3GuWYPryafwffQhhUuXYvz1rwe8Lbui/u67lWf/wKpuRYvrL6gLCyl96knc6/9Iw333seO0KdjOOYdoVRWhLVuI7NwJybQLgk6Hdtw4zMcfh3bceLTjx6EbPx7J2ruUDylIVitZF16A/YLzCX39taKFe/MtWl55Be3YMdimTcM6ZQqSzdaj68fcbpqefwHL5FYJfko4MxQEIIOJ1Ni8J3/1gYTOaFbMWAOBTn3vBI2G4gdXU37Z5VTf8Hsl4nEPEth3FyG/L0MwqrhfvEHLpk1EduxA0OmwTJ6M/Zyz0e2//6DPOQRBUNqy775UX3cdOy+4kPz5t2I799x+bVvM7abx/lU0/+lPSFlZFCxbhvX0qXu0NFA5HOTedCN1ty+k5ZVXsJ15Zr+18aeEYeLWC6QldX7/Xknc5GiU2gULUGVlkXfzzR0fk0gQ9vn22NkLgoDeZCbo7Rlxg9ZE3dVzrqV2wQJiTifZM6ZndDjRujrFb23TJiLbfkRQqzEdcwzWqVMwHX30XhECW5AkrKedhmXyZDx//gvORx6h+obfoxmjRPu0TJqEIElpM97uatyaN75C4n/fEbNZKH3y6X6XDqqSgWCann4Gx1VXoR01ql/r6wpCPmVA7uvBLO7zUzljBsH//Iei++7FMmlSj65jOfFEst5/F378Bs+X/4ZDDu/TdnYHgX//m5aNr5B95RUZRCQlwR8s0ytRqyV37lxMxx5L7a3zqbjscmznnUvejTf2mz/JntD8yqu4n3+BrCsu7/Gz7w8IokjWxRdhPOpIam6Zh+uxx1AXFaEdPx7ziSegS5o5akpLB8Q3RhAE9Pvvj37//cm9ZR6eP79F88t/on7ZchruvQ/ziSdimzYNw2GHdusbbXr2WeRgEMdVM9Pb0ulPfuYat1QQkKGmcYOuJQYXjUZKHl1H+fkXUDn7asqe+0OfBfroCLIsK+l21BqaN25U3C8++wwA/SEHk3/ZpVgmTUKyDB2fwRT0+01gxMY/UXPLLdQtuYPAl19SsHhxnwcHkmMx3BtepPHBB0n4/WRdfDGOa67ulpWB7cwzFZPuFSsxTZz4kwk81Z8YJm69QMp3KOz3Yc7efYj7nypcTzxBeMsWJRz/bjqfcCCALCe61NnvyV69K1ASda+jZv4CGletItbYSM51c/D+/R1aXt9E4JNPQZbRH3QQ+YsXYzl5Up9Jg4caBEnCeuopWE6ehPftt2l8+GFq5t6Ic+3DOGbNIlispAHojp9W03PrqV+6FP3BE2gxaAbMpCP7iitwv7AB59qHKbrv3gGpszMoYZ77dnKfSdruwzLppF5dr+j3c+Hqy2j408vEfjcNlWPg+yA5GqVu0WJUBQU4Zs/O2NcqwR/ciYvhoIMY+dqrND6wmqZnn8X/zw8pWLYU42GHDWg7gt9+S93ixRiOOILcG24Y0Lq7Cu2oUYx46UXkYHDAIjzuCZLJiH3aNOzTphHasoXml16mZfNmPG+8gbqsFNtZZ2H73e/2+P7HW1pwP7ce84knZggYUlEBfw7+6p0hlLQyGAqBjlLQtcn/CgV7PF5lt1P65BPsPO98KqZPZ8Tzz/dLqhk5FsP93rvIcgLP009TW+tCU1aGY861WKdMQVNc3Od19jVUdjsl69bhXLcO50NrCH/3PUUPru4zd4XAv/5F3V1LCW/ZguHXR5C/YAHaMWO6fR1BFClYsoQdp/+O+uV3U3Tvyj5p308ZP9/Yt30AbXJg2xsldeFt23A+/AjmkydhPu643R7Xmny7i8TN3zviBq2JurMuvRT3+vVsPeLX1N56K9GqahyzZzP67b8w4oXnsZ97zl5L2tpCkCQskycz6vXXKXpgFYIkUXPTTVQuXAiAVqvr0nWcjz5G/dKlmI4/jqxJk9L+mwMBVVYWWRdcgOettwj/8MOA1NkZepJGoTPEfT4qp08n+N//UnT//b0mbQB6exYA0WiUmlvmIScSvb5md9H03HrCP/xA/oL57Sb6KR+3oSDBF3U68ubdQtn650ASqbj4EuqWLiMRCAxI/TG3m+pr5yBlZ1N0/31d8v0aLAiCMGRI267QjR9P/u23MfYfH1B4z92ocnJovO9+fph4DFXXzsH3z38iJ806d0XTc+tJ+P04ZmVG8GxrOfNzRjAZAXawzfnaIpO4dQ3qwkJKn3wCIlEqrriSWJuIpr1Byv2ifvlyfph4DDt/PxcA64EHMeLFDYz6y5/JmT37J0HaUhBEkZzZsyl5/HFijY3sPGsanr/+tVfXjNbVUf37uZRfdDFxr4ei1aspfeqpHpG2FLSjR5M9YwaeN97A988Pe9W+vQHDxK0TeP7yNs7HHsf77rtEKiraTYz21g5fjsepXXAbosFA/m23dXpsqBsOzUpOlt4TN2hN1J238Hbs55xN2fN/ZPRf3ybn2muGVFj5gYQgilgmTWLkptcoWr2aqFqZHNbPuprm115DTkZ72xWyLNNw/yoaV63CcuqpFK9ahd5iJR6LEYuEB6z9WZdfhqjX0/jwwwNW5+4Q9vv6LJ9R3Oej8srpBL/+mqL778Ny0ol9cl1RklDr9KiPOBz/Rx/R9PQzfXLdriJaW0vjmjWYJk7E1IFwp1WoMzSCggAYDj6YUa++iv2ii3A/9xzbf/c7Al980a91yvE4NXPnEnM6KX7wQVRZWf1a388Bok6HdepURqxfz6i33iTroosIfP45ldNnsO2EE2hcu5ZoXV36+LjXS9Mf/oDp+OPamc9p9QYQBMKBn7uPm29IRZSE1r4j2E3/Q+2YMZQ8uo5YYyMV02cQ78W8I1pXh/Pxx9kxZQo7zjgT9/MvYDjoILJuXwBA7rnnoj/ggCFFeLsL01FHMvKVjWhGj6Z6znXUr1i52/nC7pCIRHA++hg/njwZ79//rgjR33wTy0kn9sm9yZ45A83IkdQtWUIiGOz19X7KGLpivyEA3z//QcvGV9K/BZ0OzaiRaMeMQTtmLDGHMgDvbU7N7vXrlXCxK+7Zoz1xa+S4gTGV3BVZ55/fp9fbGyCIIpaTTsQUbIEXnkWj11M771acjzyCY+ZVWKeclpb4y4kE9cuW416/HtvZZ5O/aCGCJGWYD6m7qLHrLVR2O/aLL8K17lFCV81CN773Sb57ipDfjzm791E0416vQtq+/ZaiVfdjOeGEPmhdK3RGE5QUYz7hBBpWrcJw2KGdRunqS9QvWw6JBHm33dbhwBzyetHo9UiqwcmHuDuIBgP5C+ZjPv54ahcsoPzCi8i65BJyrr8OUdf373rjA6vxf/x/FCy9C/1+E/r8+j93aEeNIu+Wm8m54Xp877xD88sv43xoDc61D2M6+mhsZ08j9N33JDweHFfNane+IIpo9Ya9TgDbXYR8/ZtzsSfQ90Djlj73wAMpfnA1lbNmUzX7akqeeLzLeR0Tfj+ev/2Nlk0duF9MOgnJZqPyf1/Dxv7P9TlQUBcWUrb+ORruvpump54i9N//Unj/fRkRZncH7/vvU798OdHyCkzHH0fevHl9rnkUNRrylyym4uJLcK5dS+6NN/bp9X9KGNa4dYLCpUsZ9/m/GLHhBQqW3oX93HNRZWUT+NfnNN5/P66FiwCoWLiQ7WecQfXNN3eqofspIFJZScMDqzH+9jdYTjttj8d3T+NmIujzDpj53c8dkYAfUVIxZuNGiteuQTQaqZ0/nx9Pnkzzxo0kwmFqb7sd9/r1ZF16KflLFqcDD6SdwgdYKJF96aWIJhPOtWsHtN5dEfb7ej0gx71eKq68st9IG7Tmkiy48w5UOTlUz72ReA9SbnQXvg8+wPu3v+GYNWu36TSUaLNDzzE/BePhhzFq02vYzzuXpmeeYcfpvyP41Vd9Wofn7b/ievxxbOecMxwRrZ8hajRYTj6Z0qeeYvTf/kr29OmE/vc/qq6+BueaNZh++9vd5s1K5a38OSPo8w1KBNjOkAocE+5hn2Y6+mgKly8n8K9/UT13bqdaJDkex/fhR1TffDNbjzqa2nm7cb9IRjRNjY0pIefeAFGjIX/hQgpX3EPwm2/YceaZ6Xy3HSFSXk7lzKuoumoWgihR8sQTlKxZ02/mosbDDsN61pm4nn6G0Pff90sdPwUMa9z2AMlkQn/ggegPPDBje9znI/j997yzcjGqAw9A5YsQ+OxfeF7fnD5mVw2ddsxotGPGoC4uHvCEq12BLMvULlyoOIMuXtwl9XZ3cr/ozRbi0SixSHjAtDg/Zyihio2Iooj5uOMwHXssvvfex7l2LbULbqN+2XLF5+Pqq3Fcc3XG8x4sh33JZiPr4otxPvwwoe++Q/eLXwxo/ZCKFuZD2wsTvxRpC337P4ofWIX5+OP7sIWtSOWSlGw2ilauoPziS6i7445+TauQCIWou2spmlGjyL7s0t0eF/J6hlRo8Y4gGo3kL1yI+YQTqFmwgJ3nX0D25ZfhuPbaLkvnd4fwjz9Se+ut6A7Yn7wF8/uoxcPoCjQlJeTecD05116D7x//wPu3v5M9/crdHq81GIdEWo3BRMjrJbds8CP6toWkUqHW6XvlG2897VTibjf1y5ZRt2QJ+XfckTHWhbZsoWXT63g2bybW2IhosWCdMgXr1CnoDzpot/Og1Ng4lEzB+wrWKVPQjt+H6jlzKL/0MnLnziXrskvT9yLh9+N89DGann4aQa0m96abyLrowgGJ2p1344343nuf2oWLGPHC8wMS5XaoYZi49RCSyYTpkENQqTWoDzmY0gsvBxRCF9m2TUlYuu1Hwtu2dYnQ6X7xC9QFe46a1J9o2biRwP99Qv7iRV1uS1rj1gXtRNsk3MPErf8R9vsznosgCJiPPQbTMRPxffABTc88i/nYY8i6+OJ256bOG2iNG0DWpZfQ9NxzNK5dS8maNQNefywSJh6L9ViSGvd4qLhyOqHvvqN49QOdBvfpLbRGIz6XCwDDIYfguHo2zofWYDrySKxTp/ZLnc5HHyVaWUnpM890OlB3Jb/jUIHx179m1Ouv03DPClxPPIn3/fcpXL68x2ancZ+PqmuuRdDrKV69GnEvSEPyU4SgUmE+9tg9JmRWNG57l8tDdxH0eYYkCdGZTIR6aUWQdfFFxJpcuNY9ipSVjf2C8/G88SYtr79O+PvvQa3G9JvfYJ0yBdMxE7v0vYbTGrehd8/6Arrx4xix8U/U3jqfhhUrCH75JQXLluL74B80rFxJrL4e69Qp5Myd2yVzyr6CZLORN28eNTfdpKRWuejCAat7qGCYuPUSu5pYdKah2xOhM/6/X2O/4AJMEycOuBQhWt9A/T0rMBx6KLazz+7yeUGvV9HqdKG9+qTZVNDr2SvTJww1pDRuu0IQBMwTJ2KeOHG356a0TYPhvylZLGRdegnOh9YQ/PZb9L/s2Lypv5CWpPbAVDLu8VBxxZWEvv9eIW17mDD2FjqDEVdlefq346qrCPzfJ9QuuQP9AQegGTGiT+sLb9+B64knsUw5DeMRneeOC/m82PIGVxjVHUgmEwV33oH5xBOpve02dp57HtnTr8Qxe3a3iJecSFAzbx6RigpKn34KdX5+P7Z6GH0BrcGEp7F+sJsxaIhFIsTC4UFP3dERdCZz2rKnN8i57jriTW5cjz6K6/HHIZFQtOG334Zl8mRUdnu3rhfy+0AQ0tHF90ZIJhNFD66m6elnaLjvPny/nYgcCKDbd1+KVq3C8KuDBqVdllNPoWXTJhpXrcJ8wvE/uz52mLj1ElqDsUvmZLsldF4vkR9/xP/JJ7g3vEjV1degLizEdt652M46q9udSU8gyzJ1S5YgRyIU3HlHt8w4Qz5vmpDtCW01bsPofyi5yHomDUxpmwbLfCjr4otpevYPONespeSRgY0ymfZd6GYet0zSthrzscf0R/MyoDWaMvofQZIoXLmC7af/jurfz2XEhhf6zHxFlmXq7rxDCa1/8817PD7k3XPS3KEI09FHMWrz69TffQ+udY/ie/c9CpYv67IAwfX4E/j+/g55t84b8Fxxw+gZdEYjjeU/X1PJVl/1ofe96vtA4waKwDJ/0UIkixnUasUcsBc5y8J+P1q9YUi6vfQlBEEg+/LL0O83gYbVq7GeNgXbWWcOqomiIAjkL17E9lNPo+6uuwbFMmcwsXe/cQOA3jo1S2Yz+gMPxHHVVYz5+98oenA16pISGu+7n22/nUjNrfMJfvNtH7a4Pbx//jO+d98lZ86cbkvoQ76uT87SOVn6IJfbMPaMsN/XY3O/FOEbrIipktlM9uWX4XvvPYJffzOgdfdE4xZvaaHi8isGlLSB0v+EAv6MQEjqggIKl95F6H//o2HVA31Wl+fNtwj83yfk3HD9HpMdJxJxQgH/kA5O0hkki4XCZUspXvcIcbebneecS+NDa5AjkU7P8334EY0PPIDllFOwd2CCPIyhia4KYPdWtBK3ofe96ox9F41akCRyb7yR3Ouu63WiacWiZegR3f6C4dBDGbF+PfZzzh4SfmWa4mJyrrka39/fwfO3vw12cwYUw8Stl1A6/L6Z3AoqFZYTT6Ts2WcYtfl1rGeegeftt9l51lnsPOdcWjZvJrGHiUN3EXO7qbtrKboJE8i6pPsTjaDXi66L5hWpiFV9lcttGJ0j5Pd3W2uUQipH2GD6fdgvvBDJaqVxzUMDWm93NW4p0hbesoXiBweOtEFSMyrLREKZeW3Mxx+P/fzzaHr6aXz/+Eev64l7vdTfcze6CROwn3POHo8P+XxKCO0hHpxkTzBPnMioNzZjPWUyzrVr2XHOuYS2bOnw2EhVFdVz56IdO1axXPgJ53X6uSElgE0kOk7evbcjOIQ1blqTqc/TCPUF+iLy8DB6h6xLLkG7zz7U37V0QKIpDxUME7deQonqFuj7647FSHpQAAAgAElEQVQdS8GiRYz94H3y5s8n3tJCzU03s+2YY2lYvTojuWhvUL9sOXGPh4KlS9O5vbqDkN/b5c4rpXHrC3v1YXSOVGTE3gwsOqOJkG/wpNCSyUTWFVfg/+AfBP/znwGrN6VB78q9S5O2rVspeuhBzMcMHGmDVnLZkbYg9+ab0Y4bR828W4k1NvaqnsYHVhN3NZG/eHGXpK2pidZQS+jbE0hWK4X33EPx2jXEGhrYcdY0nOvWZYQWTwSDVF07B2SZ4jUPIe7Ffi97I1IBJiKBn2di3/T3OkR93MJ+35BLI9Qbwegw+gaCWk3BHUuINTTQ2IfWJUMdw8Stl+jv/C+S2UzWxRcx6q03KXniCfQHHIBr3aNsO+54quZch//Tz3rcoXnffx/P5s04ZszocbLjkNfb5c5erdGiUmuGpPRsb0MsHCYRj/fKlENnNA5KVMm2yLrgfCS7ncaHBs6GPeVPsad7F29upuKyywlv3Urxmoc6DfbSX9AZdh/9U9TpKLr/PhKBADW3zOtxXsngN9/ifuEF7Oedt9s8WO3OSWrVu6qN/ynAfNxxjHpjM5YTTqDxgdXsPOdcwj/8oPj+LV5M+PvvKVq5Ak1p6WA3dRjdRFoA8jONLJn+XoegoEVnNBGPxYiFw4PdlAwMa9yGBvT774/9ggtwP//8gAp4BxPDxK2XUIID9L80SBBFTEcdScnDa5XkopddSuDTT6m45BJ2TJmCe8MGEt2w0Y/7fNQtWox27Biyr5rZozYl4nElAEY3zCt05r6zVx/G7hFKTkB6M7BojaZBn8iIRiPZV16B/8MPCfz7ywGpM/U3d+YfGG9upvzyywn/8APFax7C9NvfDkjbdkU6Qe1uhEfaMWPIu/VW/B9/TNPTT3f7+nI8Tt2SJUhZWeRcN6fL5+1NGre2UNntFN1/H0UPPEC0poYdZ5xJ9ZzraNn0Oo5rrh6092AYvUOKuP1cc7kN5e91qFrqhHcTtXkYA4+c669DlZtL7e0LkaPRwW5Ov2OYuPUSWr1BkQZF+9b3rDNoiovJvfFGxnzwPgVLl4JaTd3iJfzw24nULVtGeMeOPV6jYeW9xBobKbjrrh7nGEpJ+bvj0KwzDRO3gUDY17PIiG2hNZrS1xlM2M87Dyk7G+cA+bqF/T7UOj3SbkyHo3V1lF9+OZFtP1K8ds2gTtY7M5VMwXb2NMwnnkjDqgcI/ve/3bp+80svEfr6a/JuuQXJ0vXvPB3sYC/SuLWFZdJJjHpjM6ZjjsH7t79hmjgRx6xZg92sYfQQOsOev6O9GSGfF0mtRtXLpPP9gRSZHGrzhlDA/7MKTjKUIZlM5C+8nfDWrbieeWawm9PvGCZuvURa4j0IHb6o02E78wxGbtxI2QvPY5o4EfcLG9h+8mQqrpyO9733kOPtna39n35G84svknXxxegPOKDH9bdK6bqhcTOZ0mYZw+g/hJIamF6bSvajGXBXIRoMZF9xBf6P/4/AF1/0e30hX8e+C7Is07JpE9tPm0Jkx06FtP3mN/3ens6gS5t47f45CYJAwZ13oMrNoXrujV124o45nTTcvwrDEUdgOfWUbrUr6PUo7RuCwQ76CqrsbIpWP8CIl16k6IFVe31Y8L0ZrZrrwRdUDQaCXi86k3lIBtQZimmE4rEosXA4TfiHMfgwH3cc5hOOx7n2YSIVFYPdnH7F8EjTS2i7MHHqbwiCgOGggyi6dyVj330Hx5xrCW/dStWs2fx40iRcTz5FvLkZUJzoa2+/HXVJSbdMnzpCT/xY9CbLkJOc7Y1IRTrtzcCSMgMeCrCfdy6SwzEgvm7hQHvfhZjLRfWcOdTcMg/t2LGMeu1VTEcf3e9t2RNSQRX29Jwkq5Wie+8lWl1N3eIlXTLtbli5kkQoRP7C27s9oQv5vAii2ON0FD8VCIKAfv/9EXW6wW7KMHoB7bDGbUiaScLQTCOUek+0e7Fg6qeIvNtuQ5CkLo9xP1UME7deYqiZWKhycsiZPZsx7/ydogdWoc7Pp2HlSn747URqFiygbskdRCsqKLjzTkS9vld19SRpp85kGvSAFz8H9MXAojOaiASDJDrQ2g40RL0ex/QrCXzyCf7PPuvXukK75L/z/PWvbD/1NHwf/IPcm26i7Lk/oCkr69c2dBUag/INd8U3x/CrX+G45mo8b7xBy2ubOj3W/+lntGx6newrLkc7alS32xX0eoasBH8Yw9gVqTFsMAWwgwklH+vQJG4pbehQ0riF+kAwOoy+hzovj5wbbsD/8cd43nhjsJvTbxgmbr3EUNC4dQRBrcYyaRJl659j5KbXsE6diuetP9Py2mvYzj4b4xGH97qOVlPJbvq4eT17tTRkKCCdi6xXGreh9W7bzjkHVU4Ozgcf6tf3J+xXAu7EW1qovulmqudch7qwkJEb/0T2FZf3e/LRRCRCaMsWWt58k8Y1a3FveJHgN992mPxZFCU0ekOXn5Fj5kwMhx5K3Z137tYXVo5EqLvjDtTFxTiuuqpHf0PIO3Ql+MMYxq7Q6PQgCD/r4CRDlbgNRR+3YY3b0IX9vHPRHbA/9cvvJuZ2D3Zz+gXdT9w1jAy0mlgMHWnQrtCNH0/BHUvInft7/B99hKmPck21BiDoeoevM5nToX3Vw+ZF/Yb0wNIL4pYyFwz5fUMiv4+o05E9Ywb1S5cS+PRTjEcc0S/1hPw+7Hoj20+bQqypCce11+CYMQNBre7TehLhMJGdOwn/sI3wj9uIbNtG+IdtRCoroQMtp6BWo91nH3QTfol+wgR0EyagHT1aSUnSxf5HkCQKV65gx9TTqZ47lxEbNrQLTuR6+hkiP/5IyaPremwCGPR5BzUwiSzLEIv1+TMbxk8HCb+faF0d0ZpaYg0NSHYb6qJiNMVFiLv4sCpmvYafr4+bz0v+ECVuKq0WSaXqsqWOLMskWlqIVFcTra4mWpUsU0tNDaLBgGbkSDQjRrQuI0egKS7uUp/RKhgdJm5DDYIkUXDHHew48ywaVt5L4bKlg92kPscwcesl0sStH5Jw9zUkqxXL5Ml9dr2g14sgiGj1XU822za078+duCUiEeJNTcRcLuJNbuJNLmKuJuItLYg6LaLJjGgyIZqMSGYzojG5bjIhms0IWu1uTdFCe4iM2BV0JWLhQMN29jRcTzxB40NrMBx+eJ+b4sV9fkJNLiLf/YBktVP88MNdzl22OyTCYSI7dhDe9iPhbT8Q3raNyLYfFQfqVG41SUJTWop27BjMJ09CO2YM2jFj0IwYQayhgdA33xD85htC33yLZ/MbNL+wAQBBp+MgvZZorZvmwpHoJ0xAM3Jkp1pBdX4+BcuWUnX1NTTedz95t85L74tUVeN85BHMJxzfq2iZIZ8XS05uj8/vCHIkQszd3Pqd7Fq6XMSaWks5FEKVk4OmrAz1iDI0ZWXKBK2sDE1p6ZD2S0v4/USqqohUVBCtrCJSqZTIMqqcHFQ5DlQOB6qcHKRkqcrJQTQafxbmqXIsRqyhgWhtLdGaWqJ1tcTS63VEa2tJtLTs9nzJbkddXIy6qAhNcRHq4mLyglHiVdUkIpEeR1r+KUKWZcXHrRsC2IGEIAjtolHHPR6i1dVEqqqShKwmSdKU37umRhKNRuV5l5ZiOPxw5fvasQPvX/+a9v8HlH64uDhJ5EZmkDpVbm7620r7kA9yVEk5EiHW3Kz0dQ4HoqHrc7G9Gbrx48m+7FJcjz+BdepUjIcfNthN6lMME7dO4N6wgeDXX6PKdqDKzkJKl9mosrORbLYhZ04mx+PE3W5iTicxp4u4y5lejzmdxFuaURcVoRs/Hu348WjHjkMy9UwrE/J50JlM3YqmlhocQj4vFkdOj+odqpDjceLNzUki1krIYk0u4q6mdBlvaiLW1ERid9E1RbF1Qt8ZVCokoxHR3IbgJcmesXw7+7S4ca57tAPyZ0IyK6WgVoMoIUiiMtmXJBBFBEFo9S0YQtpkUasle+YM6u+4E//HH2M68sg+u7b/s8+ouXU+UYcOywEHMuLu+xC7ER47TdB+2EZ4W1KLltKgtSNoY7FMPhnN6NFox4wlXpxLVbiend4qKr2VVPm+pLLidWr+V0OZpYyjRh7FUUedR5m5GDmRIFJeTuibbwl98w3et97AsnUbtfNuVe6RwYBu333RJbVy+gm/RF1amvGdmo87Dvv559P07LMY/9+v0yStfulSEEXy5s/v1b0M+rzkjhjd6TFyIkG8paXNt5Is23wrMXdT8nfTbifiglqt9MlZSt+sHTUKKTsb0WBQJnfl5fjee5+4y5VxnqqgQCFxZW1I3YgyRerezxN3OZEg1ugkWllBpLKqtayoIFJV1a6totWKprgYJInw9u3EnE7oIF+RoNMpJM7RSuxUOY5WcudIkr7sbIReCHX6E7IsK/1obW1aYxatrSFWqxCyaK2iQdu1jxStVtQFBagLCjD86iBUyfVwthmvWYUtrEJd7yJSlZzgV1UR/u47fO+8gxyNMgHgy+/Y8sc/ocrNRV1UhLq4CE1xMeqiYtTFirZOlZ/f5+bSciSifAvNzbuUHW1TShKJ9FykdX6SjcqRjZSVLJPfRWfPOhYOE49Gh5SpZNznyyBi4yrqMJdvZvtb7yrEbJexUzQY0kTccNhhrc+uqAh1URGixbJbgUbM7SZaXk54504iO3YS2aks/k8/RQ6F0scJBgOaEWVoR4wgGo9R6PZCeQVxqw2pD0ivLMskvF5l/tbURNzdTNzdpPx2uxXhrtut9InuZuJNTSR28fsTTEbUefmo83JR5eSiystDlZervM95eahyc1E5HEP22wflPsiBgBIRXRBAEBEEkuuCMj8SBATI+I0gZDxjx+zZeP7yNnWLFjFy02vdGsuHOoSh4mt0yCGHyJ9//vlgNyMD9StW4nnjDWJNTRCLtT9AFJHsdpr9XrQFBTh+uV+HBE+VrXSgPX1x5EQiScY6IGIuJ7FGJzGXKz356WjSL+h0qLKzES0WopWVGR+8uqQE3T7j0Y4bj3b8OHT77IO6uHiPhGzzA/fQuHM7lz/waJf/lsr/fc1LS25l2u1LKZ3Q81QE/QE5kUAOh0mEQsjBoFKGQiRCIRLBIAm/P026MiaXTa50p0pH31PyPUlNLFtLuzLAZmcpZZZdeU9MJohGifv9JHy+9BL3+kj426yntvu8JHz+Nr99BBvqESNRxK4QwI4giiCKxONxJI0GUa1uJXaSiCC2LwWVBB1sRxIRdXokiwXRakGyWpEsViSrBdGS/G21IiXXBb2+U61BIhLhx5Mmoc7Lo+yF53utYUiEQjSuWkXTs39AHlHKn61qjrlkOr+aPDV9jCzLyrsQCJAIBIi3eIjs2J7Uoilmju0IWllZUnM2Gs3oMQRLsqnNEqgK11PprcxYmkJNGW2yaCyUmEvIN+azpWkLVb4qAEZYRnBU0VEcVXQUB+cdjE6l47WVd+JpqOecGdcRTJK50DffEPr+e+RwWHmcZjO6X/4S/YRfJgndfkiObMrPPoeY08nI114l9PXXVF19Dbk33UT2FZd36d7JkQhxn4+Ex6O8k16lfHvV3ZSNGc/IcfsS93qVCUmqbGlJfzMdmYQiCEg2G1J2Fqqs7I7L7Gwkux2PUaRB9FIXqKfOX0e9XynrAnU0h5vJN+RTaiml1FxKmZRDUbOIvTFEoqKKSHk5kfJyojvLlYlwCqKIurCwPaErK0NdVNTlSU8iHCZaVUWkspJoRSWRqjZlZVX62aTrLChAXVKCpqSERGEuzQ4t9TbYaQyxQ26gwqOEuM7WZ5OltZOfMJMbVJPlF7D6ZIyeCNrmIDQ1E2tsJOZsJNbo7JjwCoLSJ6UJnQNVrlJKDgeSxQrISn8my60+pbIMMhn7lM1y6z5ZJnlQ5vkd7JMjEaL19QoZq1FIWbSuDjkYzGyuWp0mYuqCAtSFBQi5OfiydLitKhrMCerkZhoCDRlLY7CRcLz1PheZihhvH8+4rHGMs49jvH08RcZCEo1O3r7zdtQ+P7869Mg0YYhUVxGrq88cU1UqpQ3tiJ2yjii2Eqy2xKuluUMSlmhuIdGZxY5KpXwPNiuS1ab0lTYbiIIy/rhcxJ3KHCDjnWr7rFPfU5LcSY5sVElyF1ar2PzEGg676AomTD2j5/OUWEwZJwNB5FCw/XowRCIYUMbWduvBpGlrLdHqmnbvbFySiJoMOA78VfK+KyRNWQqRbLY+1zTLiQSxujrFnH1nK6GL7NhJpKoKoc1YL2VnK6aWI0agbWN+KZrNxN1uZd7QhnzFm93EUutNTcSa3cTdzR3PM4GEWkXErCVgUtGihyZdlEZ1mBa9jMcAERXY/JDllckLqMn1q7B5Exg8YcT4LnMSUVTmpblJYpebkyR1SWKXp5C8zshup/dNlkn4/ZljgsebLuNeD4lkGWtpIdzSRKSlWSHjPj+iP4SY6AUvSRG8VNvjcZAkpd9OEr22pE+/3wRKn3qq5/X1EwRB+EKW5UM63DdM3HaPre6tBGNBCo2F2MOqtCYr3tSkkKgmFzGnix/+/jYWnR6TSkPc6dxtJyyaTG06z9TkXelEJaNR+ZBdraQs5nIRczbudoIjaDTpgVblaNMhOxxKHTmpbTmIRkP6I5RlmVhNDaEtWwhv2UJoy1bC339PpLw8PRALBgO6sWPR7rOPQuaSGjqpjTPuy3cuIBoJc/6d93b5njZW7OQPN13DaTfMY9wRR3XncaSRsmGPNTURczpJeL0kgqHkABEiEQoih8JKGQwlCZiyTw6Hkse0IWfBIIlwOEO6tieIVqtCwLKykkSs7eQyq5WQZWcjWSwdSmhlWcYb9eIMOGkMNtIYbMQZcNIUbiKRSCAIAgICyv/kv9S2JFK/02Xy+G/f+zvIcMBvjkMVjKIORpECYVTBCKpgFFUggioQQSOLGEQdelGLTlCjEzToBA2iDBG/j6/+8iYj9jsQR1EJxOPIiTjEE+3LeDy5P9H+uFicRChE3NNCosVD3OPpXKOoViskLknkRKslSfRS5M5C6LvvaXntNXJvvgnT0UcjJsmfoNEo5DsQIBEIkgj4kZNkS5lIBEj4U+t+IjvL8b3/PgmvF3VJCUJODnXf/w97VjYaUVImF8njOyTlkqQM1qNHoxo9kkBxFg15OsqtUSpCNVR5q6j0VVLlrSIYa52MCgjkG/MpNhdTYi6hxFySXi82FWPVWjPek3JPOR/VfMQ/q//J53WfE46H0Uk6Dsk/hOztUaxbAtx03/OZ71c0SvjHHzPMLENbtqQ1NZLNhmbUKIL/+Q+a0aOJu1wIGg05c+aQCPhJeH3KINtJucdvRhAUja/ZhGS2KKXF2iqs6Ki02UCS8EQ8ChlLkrL0EqhLk7RIIjNgi0bUkGfMI9+Yj1Vjpc5fR7m3HG+kVUIvCiIFxgJKzCWUmksptZRSJmelSZ1cWU1kZ3ma2GVItVUqRYrf1vSypIR4i6ed1ixWX5/xzggGA5qSEjSlJaiLi4kVOHBlqamxxtmh91ERrKHCW0GlpxJ3ONOpPlefS7G5GEmUcAVduEIuWsIdayCNaiMOvYNsXTbZ+mwckpWCiJ6cgAq7X8DqS6BvCaNtDiC3IXnxRidyB1q8gYCU40BdUIg6Px9VQQGxHBu+LB1NFpF6c4JatZ+GUGMGKdv1HgFoJS25htz0kmfII9eQi11np8ZXw1b3Vra6t1LuKSchK32QXqVnrH0smgofVrfIxZffzlj7WMwaRYsiRyKK5q+qSjHNS/lMVVURqa4m7nR28Y+UWoVUNltmabdl7BOtVlQ2G6LVljF2dwZlwhxQ5hCulGBXMSOOuZzEnUnhblLIu6u2JgXRZEoLm1XZ2YhWS+t4GkiSsFBI6VdTQs1gsEMNcKcQRUS9HkGvR0wuqvy8JBEuylg2P/4QXpeTi1c81OXLJ+QE8UScaCJKTI4RT8SJJWLE5TiSIKFVadFJOtSiutsE5YNnHmPr5tc4d/ZcxcoiTezKu/Q+iFYrgt1KzGwgZNbgMwi49Qmcmgh1mgBVYgu1Kj8eA3gMEFYrgahyDbkUGgvJN+ZTaCqkwFhAgbEAs8ZMnb+Oal81Nb4aqn3VVPuqqfVWo/NGyPIppM7ug6KgjsKgDodfwuqJY2gOovIG27VR0OkUIpebgzo3TyF52VkkwuEk8eqIjCnCuT1ZDIU1AgGtgFebIKADv1ZIlhDUiWAykBAFIvEIsXgEZBAAIdmdikn5T2qbIIOAjISERlSjEdWoBaUUmz1I3iCGolI0WgNqUY1aUKEWVagFFbrCYg6+fkm3nv9AYJi49RDz/jmPN7e/CYBO0lFoKqTQVEiRqYhiUzFF5iIKTYW8v/Reykb8glPn3AwoudIUnwtna6eZkoylNWMK6Ys3N2cO7mp1F4iYsl80mTrscBJyAnfITUOggfpAPfX+eqUM1NMUaqLIVMQ4uyJxHGMbg0ljSrc7vG2bQua+T5G6LSQ8nvS11UVFaMePR7fPeD7910dQUswpd67osumIr8nFo7Mu4fgrr+aAE05Ob5ej0Vb/FFfbAabtfXSl/Vd2J5lqC0GnQ9TplIFBp0v/FvU6BF1ym16HqE2WOn3rPr0OQZs6VpceWKSsbFR2W6emVAk5QVOoCWfQSWOgUSmDjTQGGnGFXDQGkiQt6MyQBqfvsahGJaoULQ9ya4kitZaTEuu2+/oaepUeq8ZKtLaJvOxiyorHY9Vasels2LSZi1Vrxaa1YVR3zb9GTiQU7WWLh4SnJSmN9ijEzuNp8zu5v7mFuCf129P5xQWhY4LVGURRIeB2GzFRpL66kpxx+2AuLEI0GJRnbzQgGgzEtWrcQpAG0UeVLc42s5/yoELQav216ckgKJPIYlNxJilLlkWmIjRSz8zxQrEQn9d/zofVH/Jh9YeUe8oBKDGXpLVxh+Yfil7VPt1HIhIhvPUHRSP37TcEv/mW8JYtux1oBa0W0WxWzGw7Ki1mRFNmGYzH2HD3Io6+/Cr2O2Vqh5p7f9TfIRlLLfWB+gyiCyAJysQl35hPviGffGN+mqSltmXpsjp8B5tDzVR4Kyj3lFPpraTCW0GFp4IKb0UGAUoR6hShKzWVUJawU+QWkqSuJk3oIuXl7TRDqtzctNZMXVxMKN+G0y5RaYmyU2yiwpfUsnoq8Ua9GfUWGAsosZS0EkpzKSUWhcgb1O19V6LxKK6QQuJcQVea0LmCLpxBZ+v2rpI8XRb5cTP5YS2WiAQIyCkTJdqWILfdlr7dQvt9yc3trpXcHxES1OqC1EVd6fGqMdDYjpADZOmy0kRsV2KWWiyarmkJgrEg25u3s8W9JU3mvqn9D0Ghtd4iUxFj7WPTmrlx9nGUmEuQxMyxLhEMZvhbAYpmLE3OkmRsN+N1R4glYrhD7oxnmHrGTaEmXCEXkXgEi8aCVWvNKC1aC1aNNaM0qU3t2x0KEXe5qPzsEz56bA1Hnnw6Fo1O0YY7U+Owk4TH2zoG6nQIBn1yrNRnrIsGfXLsTI6fej2i3oCsVRNUywSkGH4pjleK4BEjeOQA3qgPb8SLJ+LBF/UpE/UkuYolYmni5aqtIhj0YS8pSe+LJWIZhCz1O3V+2764MwgI6FQ6tJIWraRNr+skHVqVNmNdJyn7ar/5Fl9tHUdOPa/dubpgAn2tG221k5jfR5MuRoMmTI3KS4XYzE7ZSXWort3Yr1fpFSJmUsjYrgQt15CLSuyeiWNqLlLlraLGV0ONP0nqvNXU+Guo8dUQTURRx2TsXrD7oCxsoixsIj+oxeETsLTE0DUHkFwtEFa+D1mvI2HUETFoCOklAjrwaOK0qGM0qUK4VCH8WvDrIKAFv04gpJPQWu2YsvLINuWSY8hRFn0OuYZccvTKb7vWnvGuJuQEoViIQCxAIBrAH/UTiLWW6W3RAP6YUgaigfQx/qCH5h+/I2xQEbYa8Mf8xBKt88f9c/bnj5P/2K37OhAYJm49RKW3ku3N29PSi5Q0o8pXlSHBBdAmVJRlj6LIVJS5mJXSqO7Yj0yOxYi73ST8fiS7fY/q6WgiijPgTBOxhkBDmpilBr6GQAPRRKb0SxIkHHoHdp2dam91xqSh7QCVWkrNpUiipGjn6uqS2rmtaTIX2bEjPdkT9Hq0Y8eiGz8O7fh9lHLcOJBUrQQ1WUYaG/j3hvUUFZZg1eoVrZnLtXv/Fa02Q/qXqbFUStFiQdQbMkiWoNF0y/euK4jGo60kLKkdSxGw1HZnQJkwxeX2GlKzxqx0TvocHAaHUuodOPSOjG0mddcH+LZoS/Qev/YKivedwElXXZcmfW33g9Ih+qN+msPN6aUl3JJed4fcfPXpu6hyrSRMaprDzXgiuydOKlHVjsylFofekRZ8FJoKsWh6FnFQjscVczuPh+ZXXsG17lGyr7wSdXER8eYWEuGQ8i4YUou+zboBQa8nWltL/bLlRLZtw3rGGeTdOi/to1D+3694eekCJi2YTyhXy07PTna07EgvNf6ajAmBXWtXiJi5KK05Sy0OvQNR6P+MK5teXMPmL15Ge+IE/lX/L4KxIBpRw8F5BytErvgoRlpG7vadigeD1N12O0gSWRddmCZlotncoyANDTu388yt13LorMtRj86jylulLL6q9ASibf8DyuTJoXekSVieoQ0hS5Iyh97RbvLZF2gJt6RJXLpMrjeHmzOOTZG6EnMJZeZSRkSs5HsEfDooNwWpCNenz99VyyoJEkWmIkosJelrtCVnPSXyXUFXSZ4z6Oz0G+8P6CRdp2Qsz5CHQ+9ALfVvhNB3n32MTz/+M0fefoNC5pq2ssW9hZ2enRnauTG2MRlj5biscV3qzyLxSCYJCyVJ2C7PwxVytXvvUtBK2rQmVS2q8UQ8eCIevBFvO0FHWwgImDSmTIKXXI81eqj8+FMmnn4hRQWj25E/naTDH/MrBCus1JUiW23LttvbbgvEOg/cphJUmDVmTBoTGlGDSlQhiRIqUYVKUKESVXjqaprbjxIAACAASURBVPE7mxhz0GHp7aljJCF57C7bU+fueowkSMTlOKFYiHA8TCgeIhxLlvFwxnr6mFgoY38g4icudM8NIVuXnUnMTEliZlSImVVrHfDAQgk5gTPozJjfZmjs/LWtJEeW0UUgooaE2NpOURBx6Bw4DA5y9blpMpZjUAiZQ+9QtN67ELKBRPPGV6hdsID8O5ZgP/tsovFomvjJyBSZigalXZ1hmLj1AzwRj/KCe6t589XHaRK8mCaMTL/wu3aiNq2NIpOioSs2FadJXUqDp5W0BKKBtBlIipjV++szfruCrnYaFq2kTQ92eca89GCXXox5ZOuy0x+NLMvU+evSksbU0naA0kradgPUWPtY7Do7oEjrnr3wLH5RNpqRjvy0uWVGhKbdICqJCDYblpGj2hGyXYlZV81E2kKWZYKxIIFYQCmju5SxVolMansglvwdDbau73JuKN7eLExAIEuXRY4hp5WApchYsgNL/dapBi6K3UOXns2EicdzzKUzenWdR2ZcyJhDj+CE6dcAiiTYE/G0krxQc4fEzx1yp9dbwi3E5EwNqUltaiVyxlZNdoGpgCJjUZcGMTka5ceTJyPZbIx4+aU9Hx+L4XriSRrXrkWyWslZsojmQ0ZnELPvqr9mp2cnEU2m5myEZQQjrSMZaR3JCMsIRlhHUGouTWurBxNfvLmJ9//wOFc/tQFBp+aL+i/4qPojPqz+kO0t2wFFOHNk4ZEcVXQUhxcc3qEGpzuQZTk94CvBVBRSVu2rprxpB85IUxtNjHIPi0xFFJuLlYmKqYB8Q6vGLFef2+8T856gJdyiaOh2IXYd+SWCoi1vS8jaErR8Uz5qcej9jbsiGo/ii/oyTLK7iu721ZIgdVlT39/4+OXn+b8/Pc8NL2xCbDPBDMVCbG/ZzpamVu3cFveWDC1mgbGA8fbxjLWPRS2pWzVjKYIWbGonrEjBqDamyVi2LpssXVZ6PVuvLFm6LLJ12Z3eq0g8gifioSXcklF6wh5aIi0ZZcZxoWbi9NAXmkxSaNFYMGvM6aXt793t16s692kG+GTjBj56aT3X//FVJNXgf0Mv33Ub4XCQMxbeqZC5tiSvDRFUi+o0QdNKP73gGPFEnMZgY5rMNQQasGqtGcRsMAlZVyHLMhWXXErou+8Y/dabqHKGfmC8zojb0A0tM8Rh0ViwZFnYJ2sf/IlPcVVVctl1awDlJXGH3VR7qzO0ddW+an5w/8D7le+304gZ1Ub80faRKc0ac5qAjbOPI8+Y10rSktu7K6kRBEGR+pgK+G1Ja8jvcDzM9ubtGWTug6oPeHXbq+ljcvQ5iomldTTbS3yYDx/FwWfORi2pFe1cQyPhrVsIb90K0BrdKitLMfm023ns+hmU7Xcg+826vsP2RRPR5ODSgMeZOQClpHltB6G2KvNgLEgwFuyW+aBepUev0mNQGTCoDehVeowqIzn6HAwq5bdBbUibFbXVjmXpsrptvtDfSCTiRIKBdMTT3kBrMGYkpVWJKrJ0WWTpsrp8jdT3kJLmpUw2anyKieFntZ+1k8rqVfq0oKPAWJBeT5G8LF0WglqNY9YsahcswPfe+5iP7Tg/YUu4ha3ffcRXf1hNeaCKhul51Bbpqaq+iVhVK6HM0efgkC2MrP3/7L13dBv5ee/9HbQZYFDYSRAsYBGbSDVSEtW1VWWr7Xhtx3YSJ3lvkvc9OfeevOnFJ8mNfZOc+OY9N065yb2JYzvxtWN7d73rVVvtqqy6SEoiKUoUSbGBvWMAzKDN+8dwwAaSADgoA83nHB/bKIMRiJnf73me7/N9DDh56udRW9iAMksZCuiChFTOYmX52AYLnY+DhQdxsPAgfmvvb8HBOEJB3Pt97+MH3T+ARqVBY55QjTtkO4TKjMqw9w+3zw0H41hRLRP/v4NxrElk5BnyUGQsQr2+CnOdXTj5xi+izr4bRcYiZOuzU/o7XA8LaYGFtKA+p37NcwveBQw5h+BwOpBBZqDYVIw8Q17Kb2I2Q6vWIlOdmezTSDjU4nXkdXtALevlpjQU6rLrUJddF3qM53lMeiZXBHPds9246riKAB+AhbSEAq/arNoVwdfyoCyLypIsoadT60JJwmi4+ePv49IP/xVf/Lt/gDvoWRP8efweGLVGIdAizWuCMVpLx/3apkJDuBnQGcn/bXIuBgazBQatYctJsFRGrVKHVA978vck+3RihiAIFPzxH+PpG29g/L/9N9j++39P9iltidTaccoU0mBcMQ6AIIjQ5rYht2HN64N8EJPuSYy4RkKboDluLlRSXh6YJfKmQKpJ1GbXoja7dsXjU54pdM9248nsk9B///vYbfh2+XDV87/wtX/7FsoyyoSqXMY2VJVVYdueV6BT6zAXCrZmseAawMLsAu7Zp9GKq7h2bXop+7csE7iR5AMQNvWinMOsM8NKW0MBl0FrCAVgy4Ou5UHZ8ucpDSXLDeVGiDMFpZgxQ9HGLQ+XX349hNsA8zyPBe+CIM1gRkMSDVG60TbRtkaaTKkpWI1WFJqsoH/GjPxzf4LtdjdoLY2BhYFQBa1/oX+pMrIT0ECLUosZlZYyvFR2AnaLHWXmMtgtdph0Jtx+94e42vkt/Pxv/4Js5gxuNJLEZrThreq38Fa1IA9pm2gTeuNGPsE3Wr6Bb7R8A/mGfBy2HUa2PntFkLa6omTQGASJoLkUh2yHUGQqQpGxSKiiGQtDGeX7F87gw56/xeuVr8OUFd0mUk6YdWZsz96O7dlbm/OnkBosH3+yPHALB0EQISnnkaIjocd9AR9AQBaVVRGWcQrXdkZJsk9lXcS/R+oEbi5kWlNPXqewPmR5GbJ/7Vcx9T/+BpY33tjSnNJkowRuEkDSdFRz3FSESqic0fnYnbc7jmcmDWIW72DhwdBjYwO9+Ns//TXY3zoJJleN7tlutIy3hMxcNiQf0AbVyByZC8knbEYb6rLqQsHY8sBstS4/FSVVqQS36BZGShC4kUYjWGd8e14IgghVNpZntZez4F3AKDO6olonyjc6qoB5fhq4ujRIOpPMRAllRVMvgbxHAVQUNmD3r/wuSksbNqyQci4GKrUaGhnNfKEMYsVt4wBbq9Zin3Uf9ln34TfwGxhzjeGa4xqujVzDuf5z8Pg9gtOlsQjPFT8XCsxEiWMGGZnltjgoV2+MrY9RQSEZkBFeRxshx7WJZZwpNcMtHEsVt3VmnyYY1sVIsr4qJJacX/5lLPz0A4z9yZ+i/P33ZDuwXAncJIAy0MIQS78vJfTXicDv9iCD0eFF6/Mo3bEr9Pg8N4+euR48mX2CAB9YE3SZSTOu/P3fY8Exil/4xt8l8V+QvohJBHEjshVIA4358dEtH2eriNLk6qzqNc/xfj863ziNqUwNMr7xdZSYS0C89yEm/vQvAIJA/u//GSyf/lREQQfndoGkYzOHSRaxDkovoAvwmarP4DNVn4E/6AcPXpJKgce5AA1JQhPnIdYKClKyUeU6nfEwTlASDJCOJ1SM97h4wPM8OJdLEkWLQmIhdDpY//RPMPDFL2Hyb76J/N/57WSfUkwogZsELN3w3TCYLZu8Oj3wLGa+VktKLKQFjfmNaMxvXPe9RmMGJpjuuJ7fs4y4uEkllWTXmfeTKhAaDYp/9deh/q3fRv75DjBX/g6uq1dhaG5G4df+DFpb5JIWlmFCvS5yYalSEPuGU8o+TZZxKtU2BdkhxXUkR1inE/pNpKHJJpUqbl6PBzwflKSHXCHxGBobkfHZz2Lm29+G5bVXQdWFV/mkMunV3JMkpJBYyA3WuSiHMkW/QdMbTfA4nUgVR9N0Q/wdSmJOsigDTvW/lfn0aejKyzH+ta/BfecO8v/wD1Hyz/87qqANWKq4yYlUqxR4nAspn8FXUFhNqKrjfnbWcUCUSqZ2omW5OUmy4dzSJUYVkkPeb/6/UGdmYvSPvgo+sHZ0U6qjBG4SsLzi9qzArlNxiwTKaEIw4IePW2uvr7B1RBdIKQIQijYiGAik/N+KUKtR8NU/gunkSZS/8zayvvTFmOb4sS5GEolpIiH1BoAgVrh/JhOWYaBP8Z4ZBYXVLHdnfZbwMM6Y1vFEQhrEe1zyK24sI11iVCE5qC0WFPz+74Ht7MTsd7+b7NOJGiVwk4BnUWLhYZxQqTXQUvqo3xvKnjmTfxNOR7iQVFKKituSm1eqQzc3o+j/+2vo7PaYjyHH3gVCpQKpN4QywclG6JlJ7Qy+gsJqdJQeIIiUqVwnAp7nBWlzil+vhEq1KNtP/p5B/H3IbZ1QWInp1CnQR49g4YMz4IOxzzFMBkqPmwSIm9tU2TglAnYxSxeLiYMoo/IwTphz86Q+tWcezu0CoVLFFFSvhlohw0v9oZVbJRIr8FSEpI0pkzhinQsp3zOjoLAaQqUCaTCkzHWUCLweN/hgUBZBCGVMjX5rsYdcbsoMhZUQBIHCv/gLqGk6JnVOMlECNwkgFy1FU0WqlAhYZ+xZOj2dOo3G6QjLMJI5I4aSEimwYMYb0S1MjgtytCNJ4gUfDAoGLyneM6OgEA4p5lbKiVDLQ4pX3ACkTsVtcZ8nxwSfwko0mcmfCRgL8gozUxTSIFzA3hTYOCUKdgu6+KVhmsm/CacjnNslmTPiUsN++v+2/RyHYMAvO3MSQBhJkgqVAs7tBs8HoVfMSRRkCGkwPhP3OhFPyGQs9a9XymhKiXEAIfMvg/zWCYX0IObAjSCIfIIg2hb/9/8mCOIGQRB/uOz5NY+lKzqKAkGoUiLjnSg8W3CiErN7SuAWHwSDDWkWlVDFLQUWzHgj5RiFREPSdEr8jTyMMKw91Qf6KiiEQ7iOnp11nHUuXq906l+vlNGUEnsG1sUABBFSWikoJJqtVNz+CoCeIIhPA1DzPH8AQDlBENvCPSbFyaYqojb+mZJKMs6Ys3SUjAwv5AjnYiRzvHqW/lZLYxRkGLilSKVgK2NCFBSSDWlIDclxovCIySpZVNxSo8dNkNMbZNcXpZA+xPTLIwjieQAuAGMAjgP4weJT5wEcXuexcMf5TwRB3CUI4u7k5GQsp5Iy6J6xGz7rdMacVdfodNCQJDyL2T4FaZHSGVFnEAxOngXjHVbC+XeJJlUqbktjQlJ/I6igsJpnteImh/EdolQy2Q6AUipaFBRiIerAjSAIHYA/AvC7iw/RAByL/3sGQP46j62B5/l/5Hm+ief5ptxceTvWpcrGKRH4OBZ+n3dLmzO90ZwS2bN0hJWw4qZSqUEa6JToLYg3crZ5Jg00vB4PgkkeJuph5NMzo6CwGoqmn4kklYi4Bssh0ULRJoDnkz4vl3MxslwjFNKHWCpuvwvg73ien1v8/wwA0XfcuHjMcI+lNZSBTvoNJVGIN/utZOkoozElhmmmI4I5iXQLy7OShQ5tYmS4KIfGNniSew8K9czIYCOooLAa0mBMiQRIovAwC9DpDVCp1ck+lU1JFVMz1uWSpSpDIX2IJaB6EcD/QxDEJQC7ALyGJSnkTgD9AFrCPJbWpIoddyIQJY5b0cXrTaaQo5WCdPi8HAI+n6SW9iRtfKYqbnJclJdMZJJ7D/IwTqFxX4bfoYICmSIJkETBMoxsquOhwC3Ja5FScVNINlHPceN5/qj4vxeDt9cBXCUIohDAKQDNAPgwj6U1pCF1BuDGm6XKxBYqbrQJU8ODUp2SwiLxmDHzrMw2En/XspzjtnjOyf47eZxOULQRKlXqZ/AVFFazdB25ZNH3tVVY54JsZi5SKTL/VUrzLwWFWNiShJHn+eM8zy9AMCO5CeA5nufnwz221RNNdUiD4ZnRxrOLlt9bydSlirVvurE0Y0bCiluKzAiLN5yLgU6vl4VsaDWhSkGSq/6sc0E2GXwFhdU8S+NPAHGsjzyqR6L8Otn7BtbtkqXzsEL6EHXFLRw8z89iyUVy3cfSGZJeNAcIBtI+2yxFQzNlEgI3nudBEIRUp/bMI46kkFLKIfQjpv9GhpPxgkylkFRS6W9TkCvUYsLrWbjfAUIQlJFvTfZpRMRSj1vy/jYBvw9+jgv9ThQUkkHam4YkCtEe1uv2JPlM4o8UPW6U0YRgIAAfm/7fVyKJxyyyZ6XixroY2S7IYsWNTXLVX5jvKA/plYLCalKlcp0ohLE+8khWpYI5ibgOkjL5zhTSEyVwk4ilG376Z+pYFwONVgetjoz5GOJNWDEokRYuDrPIKNoIH8ci4PdLdsxUhHO5ZLsgi4mjZAfYLONUGvcVZEtoHX8GElXBYACs2yWbHje1Rgstpd+SG3UgEMSP/rIFrecGYnq/WImVa4JPIT1QAjeJIA0GAEtStXTG41zYUrUNEOa4AcnXq0cKz/PwMF7wPJ/sU9kQNg6zyJY2M+mdlGBl7BamoygQhCrplQKP0wlKqbgpyJSlBEh63+uAxeCU56GXUbKKoo1gmdjvcV3XRjHWN4+2C4MI+KIf5K1U3BRSAUl63BSWSyXTP3BjGWbLjlupoFePhOkRBk9uj6P7zjic0yzUWhVMWRTMORRM2XqYsymYsimYs/Uw51CgjNqk9uxxTHwqboCQlDBYMiQ7bqrBuVyh61huECqVYJCUxMRRwO+Dj/U8E258CulJqiRAEoGYNJVTomUr81+9rB+3338K2qKDa96LntYJVO8viOoYbMj8S57rhEJ6oARuErHUY5JaN3ye58HMcpgcdGJyyImFSQ/2v14Oc45+8zevA8ssbNmAQHy/Z9GhMpVwzrB4cmcc3bfHMe1gQBBAcW0W6o/Z4FnwwjnNYmGaxXj/AjjXSvmgRqcSArocCuYsCqacZcFdjh6kQRPXwI51u6AhSag1WsmOKWYX0z0LzboYUEb5SmBImk6qqYIoe5bTRlBBYTliAuTZUM4sXq8yqh5txY36wUdD8Cx48enfasTFbz1E51VH1IGbuAbKVZmhkB4ogZtEUCmgjeeDPOYnPZgccmJy0ImpIScmBxmwLh8AQIwXtKQax79YE/PneJxOZBcVb+lcRQODVKm4sS4felom8OTOOEaezAEA8svMOPK5bahszIfBrAv7Pq/HD+cMi4UpDxamWTinWCxMe+CcYTHaMw+vZ2Vgp6XUMGfrF6t0QjBnWh7Y6bd2SXJxMNjYqnyo5Ww/RnvmUVqfDfuOHJiyKClPTxICfj98rEfWmVRhlmTyrifWufUxIQoKyYak6Wej4rZYudLLpMcNEILMGcdw1O/zOL1oPT+I8l25sFZYsP2oDdd/1INpB4NsW+T3fDGgV+a4KSQTJXCTiESbAwQCQcyOupcCtCEnpoYY+LgAAEClJpBVSKNsVw5yi03ILTEh22bEle934/HtcRz4dGXMQQIrgeV3KjhE+bwB9D+YQvftcQx2TiMY4JGRb8C+18pQtS8fllzDpsfQ6TXIthnXvflzbh8WptjFKt1icDctBHrDj2fhX/x7iZAGDTILaLz4ldqIPn/N57mkt7RfkkpGHxQ4Z1jcfu8p1FoVBjqmceX/dCPbZoR9hxDE5ZeaQaiSPw5C3KjJdRwAkPwNpxRjQhQUkk2yEyCJgg1VyOVzvcZacbt7ph9+LoDmN8sBALUHrLj1bh86rjhw7AvVER9HqbgppAJK4CYROoMgPYyHq6TfG8C0wyVU0oacmBp0YtrhQsAvNNdqdCrkFJlQ01yAnBITcotNyCqkodas9Z5pOGbDo+ujeHxzFDuei75qxvO8YPm9xc1ZyCEqwVLJYCCIoUezeHJ7HH33JuHjAqAtOux4rghV+wqQU2yUVMpIGrTILdEit2Tt98XzPDiXXwjolgV3j26O4ea7fTjxy/VRfx7rYiQPPkIy4BiSEm3nBwEe+MJX98PvDaD/wTT626fQenYALWcGoDfrYF+sxBXXZkFLJmcG4tKCLN9MKmmgMTc2EtN7O644oFITqDtUGPPni7JnZRyAgpxJdgIkUSxJJeUXuEUz/3VhyoOOyw7UHrQis4BePI4WlY15eHxrDAc+VQEdFdlWmHUxUGu10OjCK3AUFBKBErhJhEqlhk6vB+d2b+k4nMePqcXqmdiXNjvmBh8U3AxJgwY5xSY0HLcht8SEnGITMvINUEVYtcgrNSPPbkbHZQcajhdFHaT4WA+CgYAkN3vKaEyIVJLneYw/XUD37XH0tIzD4/RBp9egsikPVfsKULgtI+LvT0oIggBl1IIyapFXurTZ1VEatJ4fwN7TLmQVRhdIcC4XjFlZkp7n0nDn6P5WrnkODz8ZQfWBgpA8MrOAxu6XS8C6fBjoEIK43rZJdF0fhVqjgq06E2WL1ThjZuIklSG3MBlnUkmajqnH1u8L4PqPe8AHeJTWZ4O2xDbmQ449MwoKq6FoI2ZHHck+jQ2ZdjBwzrCwN+TEfAzW5QQIQlbW9hRtRMDvh5/joKUiWx9uvdcHQkVg76vlKx6vP2bD41tjeHJnHNuP2CI6Fud2KdU2haSjBG4SIkgsot84OWdY3PhxDyYGnJifXBpIbTDrkFtiQvmuXOQUG5FbbIIpm9pyRajhuA0Xv9UFR/cciqozo3qvR0J5BWU0hYZ5x4OZUdeiycgYFqZYqDUq2Hdko2pvAUrrs6HWpuY0jF0vFuPBx0O4e6YfL//S9qjey7oYZBeXSHo+Gp0OGq0uaqnkvQuDCAaCaDxZuuY5itaien8BqvcXIBAIYvTJHPofTONp+xQuf28al7/XjZxiI+wNObDvyEFeiSmukko2DSQwFB3boPTBzhn4WEGy23ZhEId/ZltMny9KmOTUM6OgsJpYEyCJgnP78JP/cQ+s04cv/dmBmHuGPU5h5iKhSs11MByhFgsXE1HgNjnkRPftcex5uRTGzJUJqfwyM7KLjOi44kDd4cKI9lUcw4CUUaCrkJ4ogZuECBKL6CtIV7/fjaGHMyipz0bNAasQpJWYYs58b0ZlYx6u/UcPOi4NRx24hSyEJai46Y0myStuzCyLJ3cm0H1nDFNDgiNkUU0mmk6XoXx37pbNPxKB3qRDw7Ei3PtwEHtfsYfkHZHAueOzsEQrH/IwXnRccWBbBL2CarUKRTVZKKrJwqHPVmJ2zI3+B1Pob59Cy5l+3P2gHwbLoqRyZy6KajKh1UkrqVzqcZPvokzSxlBFXKWO/PvpaZkARWtRsj0LnZcd2P1SSUz3Ho9zQZARkfG5bykoJALSEFsCJFFc/1EPPE4fCAJoPTcQVY/WcljGKTsjIXHfwTJOmLI3rzbefKcXpF6DPSfWJjMJgkD9URsu//tjjPcvoKDMsunxWLdLmeGmkHRSfxcrI2KZozTWN4+n96ew77Uy7H2lLE5nthKNVo3aQ1bc+3AIzCy3JhO1EZ5QVl2aitvUYP+Wj8O6fOhrm0T37TE4nswBPJBXasLhz25DZVNe3ALgeLLrpRK0Xx7G3TP9eOkrkVXd+GAQnNsdF6kaSRtDM+Ii4f6HQ/D7gmg8aY/qcwiCQJaVRpaVxp4TpfAwXgx2TOPpg2k8aZnAw2ujUGtVKK7JhH1HDuwNOaAztv73DRlryLjiFjJIcrsi7jPzLxr0bNubj90vl+DJ3Qm0nR/E4c9GX3UTe1+TOcdQQWGrkDQdUwIkEQw9msHDa6PYc6IErNuPrmujaDplj+keyDJOULTMAjd6KXDbjOFHMxjsnMHBz1SCNIQfj1O1Lx/Xf9SDzsuOiAI3zsXAYN78dQoK8UQJ3CSENNBgZmYifj3P87j5bi/0Ji12vrA1e/1o2X7EhrYLg+j8xIH9r5Vv/oZFQnIoCQwIKKMxFAjGyr0PB3HjnV4E/TwseXrsfaUMVXvzkZEfvSNjKmEw61B/1Ib7F4ew93RZRP8ezuMGeD5uFbdIpZKsy4cHl4ZRsTsPWdatnYveqEN1sxXVzVYE/EGMPJkLVeP626cBPEZuiQn2HTko25ETs7lMaLCqjCtuy0eSRHp9DnROw8cFUNmYh4w8A6r356PjigO7X46+6uZxOpUZbgqyJ5YESCLwcQFc+u6j0Drnmvei69qokGh5K7ZEi8GSEYczjR9LbtQbr0U8z+PG270wZpJoOL5+/5qO0qBqfwEe3RjFoc9uA0VvPP+Uc7mQaY2sH05BIV7IR9wsA0jaGJVUcvjRLByP59B40h6xq5FUWHL1KN2ejYdXRxAIBCN+HyuhE5XeZA45RMWCx+nFrXf7UFiZgc/+XhO++CfN2PdqZEGOHNj9cilUGhVazvRH9Hqx2huPqhFFGyOWSrZfGoaPDaDp9Nretq2g1qhQXJuFI5+rwpf+6wF8/qv70PxmOdQaFe789Cl+8PU7+P6f3Q6NxIgGzu2CWqOBRie/6qyIGHRGI2ntaZmA3qSFrUrYwDWdtiMY4NF2bjDqz5fCbVZBIdmkwkzWcNx6tw8LUyye/3ItNDo1LLl6VO/LR+dVB9wL3qiP53HK73oV9x2bJXx7WycxMeDEvtfKodFuXDWtP2pDwBfEoxujm35+PFybFRSiRQncJCQabTzP87j5Ti+MWSTqjyYng1N/zAb3ghdP701F/J6lHret37wo2gg+GITX49n8xWG4/9EQ/P4gjnyuCnml5rSTaBnMOtQfseHx7XHMT27uVhrPqhFFGyOquHlZP+5/NAT7jhzkFMVvU0AQBLILjWg8acdnfrsRv/iXh3Hkc1WYdrhw/6OhqI/HMcKCLOffkFhpjbRv1McJMsny3XlQqYWlwJJrQHVzATquOuCa56L6fJZxymomlIJCOGJJgMSbsb553P94CPXHbCjctlQlazxlR8AfxP2LsSRaFmQ1CgBYatHYSCoZCARx891eZBXSqG4u2PSYOUVGFJRb0Hl1ZMMksjC+R3GVVEg+SuAmIaSBBud2R1RB6ru3mBF6tSxp7oYl27NhzqHQfmk44vd4GCe0lB5qzcaSgkhYajSO3lnS6/Gj/ZID5btytyzHS2V2nyiBSk3g7pmBTV8bz4obGaFjYcdlBziXH02n7JKfw0boTcIsPvuOHLSdGwDL+KJ6P+uWfnB5ohHP7nPXygAAIABJREFUP9Kq/0DHNPzeICob81Y83nSqFMEAj9Zzm//mluNxym8jqKCwmlACJEWGcAd8QXz07S4YM0gc+FTFiucy8g2obMpH+yVHVPe8gN8Pr8cju0SLhiShUms2HE3TdW0U8xMeHHizIuIxP/VHCzE37obj8ey6r/F6POD5oKzl9ArpgRK4SQhJ0+D5IHzsxhWkYJDHrXf7kFlgQPX+zTNC8UKlIrD9qA0jT+YwPRJh/5JzQTInKrEfJhZnyY4rDng9/rBW8+kEbSGx/XAhHt8cWzEqIhxcqOIWJ6mkywU+uL6s1ucN4N6Hgyiuy0J+WXJ6Q5rfLIeXC6AlyqCDczGyHr4NLN9wRlYp6GkZh96sW5HBB4SqW01zATqvjkRcdeN5XpFKKqQFSwmQ1Ki43T3Tj9kxN45/qSZsS0XjyVL4uEBUSgMp3aETiTD7dP35r17Wj9vvP4W10oLShuyIj1vRmAeK1qLjyvrz+8SEmFJxU0g2SuAmIZFunB7fHMPsmBv7Xy8PSZSSRe1BK9QaFTouRzZwlHUxkjlRiXLLaA1K/MsChOWDq9OVPSdKoVIRaDnbv+Hr2DguLKRBSEp4WXbd1zy8OgKP05fwattysguNqNlfgPaPh+GcWf9cV8OlQe8CFYXEy8v6MdA+jcrduWGz0o2n7FFV3bwewYVPMSdRkDvRSo7jydSwE61nB1DdXIDS7eEDkWybEeW7c/Hg42FwHn9ExxX/bXJMtFBG07pSyQcfDcGz4MXBT1dGJXvXaNWoOWjF03tT6yarxO9MqbgpJBslcJOQSDZOAV8Qt9/vEwZr785N1Kmti96oQ2VTHh7fHIOX3fym73EuSCavEAf1slEO4e66PgqP04fGE+ldbROhM0jUHS7E4xtjWJhav+rGxXFhEWfXrCdRCfiCaDs/gMJtGWsqOIlm72tl4MHjzk+fRvweISEh78BNS+lBEKqIJK0D7dPw+4KobMoL+7wlVy9U3a6MwDW3edVNlDvLcSOooLCcaBIg8SQYCOKjbz8CSWtw+Gc2do1sOmUX2gc+jqztwbN4vcqt4gYsBm6utYGbx+lF6/lBlO3MQUF59Jb92w8XIhjk0XVtJOzz4u9B7uuEgvxRAjcJCdkIb6C/7rjqADPDofnN8pQxQmg4VgQfF8Djm2ObvpZlGMlu9pFa+y4nEAii7fwgCsrNKKySl5XxVthzogRQYUMJIOd2gSBU0FF6yT9fXKzW6/voujEK17wXTaftkn92tJiz9Wg4WoRH10cxMxrZ5otzueIyRiGREASxOCh98+upp2UCBosOBRXrX0ONp+zgg5FV3Tyi26xScVOQOdEkQOLJvQ+HMDnoxNHPV4MybtxTnltigr0hG/cvDkWUgA1V3GR4vQpjhNbe41rODMDPBdD8ZkWYd21ORr4BxbWZ6Lw6gmBwrU9ByPxL5uuEgvxRAjcJIQ2CDf16mTov60fLmX7YqjJQXJuVyFPbkDy7CbklJnRccWxqrOKRsI9lSSoZecWt5844nDMs9py0p0zgmwiMmRTqDhbi0fXRdSWArIsBaTCAUEl/WW+UlAgEgmg9N4D8MjOKajIl/+xYaDxVCg2pxq2f9G36Wp7nhYpbHAaXJxqxF3EjvKwfAx3TqNiTt2HzviVXj+oDi71um1TdQvMdZZjBV1BYTjQJkHgxN+7G7fefonx37hrzoPVoPG0H6/Jt2KclIqpc5HjP04eRSi5MedB+eRi1B61bMiurP1oEZpbDQMf0mudC5l8y/M4U0gslcJOQJRvh8NbtDz4ahsfpQ/ObFSkVdBAEgYbjNsyMuDDaM7fu6/hgEJyEFTe1RgudXh9xxY0P8mg5O4BsGw17feSNx+nCnkUjlpaz4SsgnMsVN/19qDoaJnDrvjUO5zSLptOpE0zrTTrsfqkEfW2TGH+6cWLAx3rAB4NpkUkVNpwbB25P708h4A9iWwQbwqbFqttmZi9in6rcXOoUFMIRqYtuPOCDPD76Thc0WhWOfr4q4vcVlFlQXJuJexcG4fduPMtyyZxEfhU3kl5rTnLrvT4QKgJ7Xy3f0rHtO7JBW3Rhe/5D5l8GJXBTSC5K4CYhITeqMJtb1uVD24VB2HfEpr+ON5VN+SANGrRf2shVyQ2eD0rmKgls3Gi8mqcPpjA75saeE6UgIrT5TSdMWRRqD1rRdW0kbNWNi6OlvRjUrN7MBIM8Ws72I6fYiNIUC6Z3vlAMvUmLG+/0bFhJFs2E5G5OAgh/p83MkXpaJkBnkBHdh8w5etQcKMDDqyNgZtevuokZfKXippAOCKN9khO4dVxxYLRnHod+ZhtoCxnVe5tOl8Hj9KHzk/B9WiIexgmVWg2dXnpZfbyhjEb4WA8CfkESOjnkRPftcex8vhjGzOi+r9Wo1CrUHS7E4MPpNf3krMsFEERIWaWgkCyUwE1CQlLJMBun1nMD8LJ+NL+xtYxQvNDqBFelvrbJDVyVpLcQpujIAjee59Fyph/mHCpi6Ug6sudEKcADbWEqICwTP0v79SpuPS3jmJ/wpFS1TURHadB02g7H4zkMdc2s+zox0ZIOEhihUrB+BZvz+DH4cBqVe/IiTn6Eet3Or191C/W4KYGbQhpA0ZsnQOLBwrQHN97uRXFdFmoORD8qSDSHajs/iIBv/dEtrNMJymhKuXt2JIj3GPE+d/OdXpB6jdAHLgF1hwtBEAQ6r64Mfrk4tiIoKESD8guUELVGC42OBLsqU+ea4/Dg42FU7ctHti11N4f1R20IBnk8XCdbFw8nKspkimgcwPDjWUwMOLH75dKkj1BIJmIFpPPa2gpIPCtuOkoPEMSKoIAP8mg5M4BMK43yncl3SA3H9sM2mLIp3Hi7F3yYhnNgKdGSFlJJg3HDSsHT+5MI+vl13STDEUnVjWWcIA00VGp11OesoJBqkAbjhgmQeMDzPC7/+2PwAI7/bHXMQVXTaTtccxy6boyu+xqWcco2ySKet4dxYvjxLAY7Z9B40g7SsLGBS6QYMynYG7LRdX1kRfAr9JCn7v5N4dnh2d0BxwmSpuFdtXG680E/+ACPfVvUX8ebjDwDSuqy0HnFgUBgbbZuyYlKaqnk5gtky5kBGCy6mLKQ6UbjKTsQxJoKSDwXFkKlArVKhtd3fxIzIy40nUpd6apaq8L+18sxNcSgp3Ui7GvEKmI62DyTNL2u8ycgyCSNWWTUA9I3c5iUckyIgkKyiaRXVGoe3xrDYOcMDrxZDnNO7BLGoppM5JeZ0Xp2IOw6DghBj1wDN/3ifdrjdOLGj3tgzCTR8JxN0s+oP2aDx+lD772lNYNLg5ExCumBErhJDGlY2dQ8P+lG1ycjqDtcCEtu6uvJ648XwTXvRf+DqTXPLTlRSXfD1xuNm85xG3s6D8fjWex6oQQarZLRN+foUd0sVECWy1o5lyuucj/SuJSF5nkedz/ohyVPj8qm/Lh9phRs25uPbBuNW+/2hd3IiBu0dOhxoww0/ByHgN+35jnW5cPQwxlBJhllNt+co0fNQSs6P3GAmV3bX8lK6DaroJBsVq/j8ca94MUnP3gCa4UFDceKtnQsgiDQdNoO5wyL7lvhR/ywjFPSBGwiEfcfA+1zmBhwYt9r5ZLvC4prsmDO1aPzypL6iI2j+ZeCQjQogZvEkDS9Qip56ydPoVITaHrFnryTioLS+myYsqiwJiWeePS4Gc1gGQZ8cH09fuvZAZAGDbYfLZTsc+VO46lSBIM82s4NAgD8Ph/8Xi6ucr/lDfsDHdOYGmLQeLJ0Q0v5VEClItD8ZgXmJz3ourZWPiRWfNMhm7qRs+3T+1MIBviYA+3Gk6VCpTeMqynLOJUZbgppA0Ub4ePYkAFGvLnyfx7D7w3iuS/XSKJeKK3PRm6JCS1nBhAMk6zyME5QtJwDNxUe3/Ygq5BGdbP0KhxCRWD7kUKMPJnD9IiwPigVN4VUQQncJGZ5pm5qmMGTu+PY8XxR1O5QyUKlIrD9aCEcj2fXDC8OmZNIePOijEbwfBBe1hP2+WkHg6f3p7DjuSLoKI1knyt3LLkGVO/LR8dVB1zz3JLBRhwXFmrRhlmstpmyKFTtl4d0tbQ+G9ZKC+68/xQ+bqVVtigt1BlSvyK+GRs52/a0jMOUTSGvNLYNmzlHj5pD1sX+ypVVN2EjqGxqFNKDpQRI/KtuvW0T6G2dxN5X7cgskCbxRhAEmk7ZMT/pwZO7ayXiQqJFnoEbaTRCrauHxykk5OKVOKw9aIVKQ4SqbpyLUSpuCimBErhJDGmg4fUIN/tbP+mDjtJg98ulST6r6Kg9WAiVhlgzyNPjdIKkpTUg0C9m6UVXutW0nh+AhlRjx3PFkn1mutB4yo6gP4i2C4Oh4COeC4vYPzX8eBbjTxew52Qp1DIxiiEIAgferIB7wYsHHw+teI5zM4Kxhkr+Mtz1xjawjA/DXbOobIxeJrkcseq2epYg63SGrmUFBbkTSoDEOXBjXT5c+V43coqN2PWSNK6IImU7c5BVSKPlTP8KYya/1ws/x8lW2qxSkdDoD4C2eGFviN8IGr1Rh8o9eXh8cxQ+LgA2juZfCgrRII9dl4wQbYRHe+fR/2AKu18uAUVL43aUKAzmxRvWjVF42SWpSDycqEI282GcJRemPHhyZwLbjxSCMsrrO0wEGfkGVO0rQOdlB+YnhD7BeAZuFC04FrZ80A9ahkYx1soM2HfkoPXcIFjXUg8Yx6RPJlX8d6x2tu27P4lgkN/yKA1ztlB1e7hslmAwEADndsnW7EBBYTXrJUCk5tqPeuBhfHj+y7WSJ8EIldDrNjvmRm/bZOjxeLhDJ5L2Sw4QKhrZhWNxH2dQf9QGLxvA41sj8HMcqDRwHlaQP0rgJjGiVPLmO73Qm3XY+bw8K0UNx4vgZQN4cmc89Fg8DAhEnX04g5K284MgCGDXC9JmItOJptN2BPxBPL45CyC+UkmSNoJzm+DonsPul0tlaRTT/EY5vKx/RZ9WOmVSqZBUcuWGs+fuOMy5euSWbP36bTwpzBIUHSbFpItczQ4UFFYTkkrGMXAbfDiNR9dHsfvlEkmuy3BU7MlDRr4Bd8/0g+eFqls83KEThYfxovX8IFTEEFTE5OZv2CIFFRZk22h0XBbUR2QazPpUkD9K4CYxJG0ECBtGnsyh6ZQdWlJ+m1sAyC8zI6fYiPZLjmU3fOkNCESdvWdVT45rnkPX9VHUHLDCmCmP/sBkkJFvwLa9+ejv8AKEPq5zZijaCELbCMqoRd0ReRrFZNuMqN5fgAeXhkN9WunUdL7Um7N0PXmcXgw/ntuyTFLEnK1H7cGlqlto+LYilVRIE8TKyvLrSEq8rB+XvvsYmQUG7I2jcZlKRaDxVCmmh5mQU3Q83KETRcsHA/BzAdDmng3HnkgFQRDYfsSGaYcbhDpfqbgppARK4CYxOr0BGv1h0BlabD8sz80tINywGo4VYdrBYKx3HkB8DAjECt5qqeT9i0MIBoLY/bJSbduMxlN2BAM8NFRjXMcBeDkT1Fo7th/OhVYnz4QEAOx7tQw8z+PO+08BCFn1dBi+DQCUYW3Fre/eJHgJZJLLaTxlF6puZweWKm4y3AgqKIRDrMCzcaq43Xy3D85ZFs99qSbuyoWqvfkw51C4+4FQdQu56Mrsel2Y8qD98jBqD1pBW4iw7RXxoHp/AdRaAmpyp1JxU0gJlMBNYuanDFBp8lF/JAtqrby/3m1786HTa9C+KBMQZr9Im1UPLZDLzElYlw8dlx2obMxDRp5B0s9LR7KsNLIKvFCTuxAM6uL2OSM9JPggC3uDvN0XzTl61B+1oev6KGbHXGBdTFwD3kSiIUmo1OoVpgpP7k4gI9+AnCLp/o2mLAq1hwrx8NoIZsaExI5iTqKQLsTTVXK0Zw7tl4bRcLwI1soMyY+/GpVahcaTdkwMODH0cEa2PW633usDoSKw99VyQbafgIobAOj0GhRWaqHWVYNQKfsRheQj78gixQgGgnj6AAgGpmCtSO3ZVpGgJdWoOVCA3tYJMLOeuAx4Vms00OkNK7JnHZeH4eMC2HNSXm6cySSrcAqAFp1Xwg9c3SpTw05MDQN+rhXBwNoZYXKj6ZQdGp0at97tA+ti0qbiRhAESAMdyqq7F7wY6d66m2Q4Ghevzyd3hM1tugS/CgpakgKhUkne4+b3BfDRdx7BlEmh+Y1ySY+9EdXNBTBmkrj7QT88Tvn1uE0NO9F9exw7ny+CMZMEZTTBwyQmcAMAa7kfBKHFaG9g8xcrKMQZJXCTkEc3x+CaC8LvuQ6vR/6bW0BwVQoGeLRfFowIKKP0WXXKaAoFbj4ugPsXh1HakI2cIvksLMmG4GehQj8eXBpe4ZgoFS1nBqDREQhwbQnpLYg3epMOu14qQW/bJAL+zLTpcQOEaoFYKehrmwDPQ1KZpIhYdRvrIwDCFJd7g4JCMiAIAiRtlPxed+en/Zgbd+P4l6oTOpdUrVFhz4lSjPbOY2rYC7VWC41OPr3jN97uA6lfGq2kNxrBMQz44Nrh4vFAS7oR9I+gr80Z6vlXUEgWSuAmEX5fAHfef4qsQhJBX88aO265kllAo6gmE4+uTwAgoI9DVp0yGuFZDNwefjIC1uVD4wml2hYNnMsFUt8NHxvA/YtDm78hCmZGXehpnUDVvkyA5+JukZ0odr1YDIrWQKM/DF2aVNwAgDQsyYie3J1AZoEBWYXx+feJVTetoRk6vbwltAoKy6EMtKRyvMlBJ9rOD6LmoBUldfGbP7YetYesMJh1GO83Qm80xd1KXyqGH89isHMajSftodFKlNEEng+CS1CCnHMx8HMPMD/JYaR7LiGfqaCwHkrgJhGdV0bAzHJoOlUEAPCmSeAGCKMB3At+qLTlcXGO05vMYBknAv4g7n04iMJtGQnR/qcTrIuB3hRAxe5cPPhoSNKqW+vZAWi0Kux8zhb6rHRAR2lQdzgLam0J3M40CtxoGqzbBdc8h5Ee6dwkw2HKomDOnoVaWxea66agkA4sr1xvlUAgiI++0wW9UYtDn6mU5JjRotGqsfvlEngYI7QGe1LOIVp4nseNH/fAmEmiYXH9AZb689gEySVZFwOC7wNp0KDjiiMhn6mgsB5K4CYBXtaPu2f6UVSTCftOYShxvNyokoG9IRsULbgqxaOPhaKNYBknHt8aAzPLhbL4CpHDuV2gDDSaXimDlw3gwUfSVN3mJ93ovjOO7UdtsOQLwTSXwN6CeFNco0EwMI+nD1Tgg+khgaEWZ0n2tk4CPFARB5nkcgzGfoDAitl4CgpyR5zJKgX3LgxiaojBsS9Uh6pGyWD7ERsIwgt/oD5p5xANva2TmBhwYt9rZSvcN8V9SKKcJTm3CxStR81BK/raJuFe8CbkcxUUwqEEbhJw/+IQWMaH5jcqoNHqoNZo4uJGlSxUahUKyoNQa+3wsdLr4imTGR7GhdZzA8gpNqK4Lkvyz0h3OJcwRDqnyIjyXbm4/9EwOPfWq26tZwegUhHY/VIJ1BotNCSZNjJgAPBzLvjZ61iYCqKndSLZpyMJYqWgp2UcWYU0sgvj27/n56ZB6h3ouj6KhWlPXD9LQSFRSFVxmx1z4c77/ajYk4vy3bkSnFnsaEk1NJrH8HE5GO9fSOq5bEYgEMTNd3uRVUijutm64jmKDj9GKF5wjGBgVX/EhmCQx8NrIwn5XAWFcCiB2xbxMF60XRhE2c4c5JeZQ03NibKqTRRZBQx4PoC+B9Jv2vVGI3xcAeYnPGg8aZeN9j6VYF1MaLRC0yt2eD1+PPh4eEvHdM6weHRzDHWHrKAtQsBOpdlvm3UxCHofwZKrw613+xAIJKbZPZ6QtBGcGxjtnY+LKclqPIwTmfkTAAG0KFU3hTRhea9orASDPD769iNodCoc/Xy1RGe2NQLe+1Cp/Wg505/sU9mQrmujmJ/woPnNCqhUK/cEoYpbgtYi1u0CaTQiI9+AoppMdF51IJgmCg0F+aEEbluk9ewAfFwA+5dZ+5IGAzh3erhKigR8Cwj6etBzZxo+r7SWuCRtgprcC0sulfSMpBzheV4Y1bAYuOUWm1C2Mwf3Lw6B8/hjPm7bOWETvnuZUYyU8qFUQMio82g8ZcP8pAdd10aTfUpbhqKN4FEKxMlNcjWscwHGDBLbDxXi0TWl6qaQHoi9oluh4/IwxvrmcfitbTCY4zdjM1J4ngfHzCCniMHT+1OYGk7NJJyPE8zerJUW2BvWGrkkuseNczGgFg2s6o/awMxwGOycTshnKyisRgnctgAzy6L9kgPV+wtWyJFIg3RNzakCyzihVnWD8/jx5M64pMd2O01QafJQezBzTWZNYXO8Hg94PhgaGgsATaft4Nx+tH8cW6+ba57Dw2ujqGkugCmLCj1OGaW3yE4m4sJf2VgIa4UFd95/KnliItGQBhpqXRUyrXpkFsTXdIXneXgYJyijSZi7qBJGRygoyB3KQMPPcQj4Y5OcL0x5cOOdPpRsz0L1/gKJzy42fByLgN8P2zYeWkqNux/0J/uUwnL/4hDcC14c+FRlWAWOqC5JmFRysRUBAOw7c2Cw6BSTEoWkoQRuW+DOB/3geR77Xi1b8Xg6SiU9jBMU7Ua2jUb7pWFJZ5kMP1aDDzphLVd+jrHAuYXf2vJZZHmlZtgbsnHvwyF42eirbvcuDCIY5NcMQScNdHoFbi4Gaq0WWpJE86cq4F7wSmbskix4GKDS2FBcE3+nTD/HIeDzQW8yw5hJCVW366NYmFKqbgryRkyExaKe4Xkel/7tEQgAx79YkzLyfzHQMWWZsON4EXrbJjAzmlpJZg/jRev5AZTtzIG1whL2NRqtFlqSSljgtrwVQa1Woe5QIQY6plPiPjfQMY2L3+5Cb+sEAn75S/0VNkfZKcfI3LgbXddGsf2IDeaclfOL0k1OBgg3fL3ZhPpjRZgaYjD+VJrG5pGeOcyOBeFn74LzpE9AkEjEqtHyihsA7H21TKi6XYqu183j9KLjigNVe/NhyTWseE7ocUuf37bgFiYsyIWVGbA3ZKP13GBchpgnipkxQZJVUK7e5JVbx8MI9wFRurTnpF2ouim9bgoyR7wvxJKEfXRjFENdszjwqYoVioVk43EKgQ5lMmHni8XQaFVoOduf3JNaRcsHA/BzATS/UbHh6yijKSFSydWtCABQd7gQBIS5s8mCD/K489OneP9v76P71hjO/mMHvvU713D1B92YGk5MQKuQHJTALUZuv9cHtYZA02n7mueEHrf02dwCAOt0Qm80oWpfPrSUGh2XpZEJtJ4dAGlQI8C1Jyx7lm6Iv7XlCwsgVN1K67Nx70J0Vbf7F4fg9wXXVNuA9Ksmc8xSJhUAmt+sgJf1y9rafvxpEEH/OLTa+M9VEzeCepMQuBkzSWw/bFOqbgqyhwwFbtGt5a55Dtd+2ANrpQX1R22bvyGBsOL1SpugN+pQf9SGJ7fHMTeRGj35C1MetF8eRs1BK7IKN1YMCLL9+O8ZwrUimLIolDbk4OG1kaRUubweP878z3bcfu8pqvbm45e+cQSv/vpO2Koz0XHFge//2R384Ot38ODjYVknIRXCowRuMTA55MSTuxPY+Xxx2IZjwdUtNW6EUuFhFkAZTdBRGtQ0W/GkZRwe59ZmmUwOOTHQMY3tR/IB+JXALUZE6SJpWLvQNb1iB+vyRRxosy4fHlwaRsXuPGRZ1x6PpI3gPG7wwfSQZLBu14oFOdtmRPW+Ajy4NAxmVn4DpRemPJgd8yHg7U7I2AbxmtUbzaHH9pwoBaEiUt61TkFhI8T7aTTXEc/zuPK9bvh9QTz/5VoQKdazLQY61GKiZddLJVBpVCmTqLr1Xh8IFbGm/SQcwvzX+CcRw7UiAED9MRs8Th/67k3G/RyWMzvmwg//4i7626dx+LPb8OJX6qCjNCjdno2T/6keX/nzwzjyuW3geR5Xv9+Nf/mdT3Dunzow0DmtOGGmCUrgFgO33u0DadBg98slYZ8nDTT8Xg5+X/pkOliGCcmh6o/ZEPTz6Lq+NQe+1nMD0FJq7HpRuEmL2XuF6BAzwuGGoxeUWVBSl4W2C4PwcZubbrRfGoaPDYStJAOLixfPp01ignMxaxbkfa+VCTKU958m6axiR5xFF/R1J0TSKgZuy397xkwSdUcK8ejGmFJ1U5AtoR63KK6j3tZJ9N2bxL5Xy5CRb9j8DQkmJJVcXMtpC4m6w4V4fDP51+rUsBPdt8ex8/kiGDM3l5cKUsn47xnWa0Uoqc2COYdCZwJNSp7en8QP//wuPIwPb/znXdj5QvGa/knKqMWO54rxuT/Yh7f+YC/qj9gw/GgW7//NfXznD67j5ju9KVNhVYgNJXCLkpGeOQx0TGP3yyUgDdqwrxEvcG+ayCUDfh98rAf6xZt9lpWGrToDHZdjn2UyN+5Gb8sEGo7ZoDeRi6YXSuAWC+LGgjSEH7S899UysMzmVTcv68f9i0Ow78hBTlH4Yy017KeHXJJzudZUKs05etQftaHr+ihmx+R1Dfe2TCC3mAYfnE+IXHupZ8a84vE9LwtVt7tK1U1BpkR7rxt+PIuPv9OF3BITdr1YHM9Ti5mlRIsp9Niel0sAAmg7P5is0wLP87jxdi9IvQa7X14r0Q9HohyO12tFIFQEth+xwdE9F3eDFz7I4/b7T/HB37fDkmfAW7+/F7bqzE3fl1tswpHPVeEX/vwQTvxf9ci2GdF6bgD/9tWb+PFftaDr+mhM5mXxJBgIYm7CDb9P3u7O8UST7BOQEzzP4+Y7vTCYddjx/Po35pDEwuWCwZKRqNOLG2LGafnNvuFYEc7+YwcGO6Zh35ET9THbzg9ApVaFvkfKaAzp7xWiQ1y8dAZ92OcLyi0ors1E24UB1B+3QasLb1rRcdkBzu1ft9oGLC1eLMPAEv8RYXGHdTFhK5WNp+zouj6KW+/24eSvNCThzKJnftKNiQEnDnyqAo5OTUJ6EVmnYE4i9riJiFW4W0G6AAAgAElEQVS3zssONJ60w5Ib/repoJCqUIbIe9y674zh4re6kJFvwKlfbYBKnZo5cZZZgJakoNEuJZ2NmRRqDlrx8PoIGk/ZYcwkE3Y+fJBH371JtJwdwOSgEwc/XQmKDp8QX41YceN5Pq6unRu1ItQetOLWT/rQedWBI29VxeXzOY8fH/7LQ/Q/mEJ1cwGO/2w1NOus4euh1qpQ2ZiHysY8MLMcHt8axaMbY/jo21248v1uVDbmofagFdYKS8IcUINBHgtTHsyMuIT/jLowM8JgdtyNoJ+H3qRFw/Ei1B+zQW9M/gzEVEIJ3KJgsHMGoz3zOPr5qnU3v8DSBZ4uFTfP4uaMWrY5s+/MAW3Rof2yI+rAjZll8ejmGOoOF4K2CItEomQP6QjnZkAaaKhU6/8m975Shh//VSs6rziw68W1El+fN4B7Hw6ipC4L+XZzmCMIiFnodBgJwAeDixW3tYGbwazDrheLceen/RjvX9jwO0kVeloEmWRlUx5u/jAxsyQ9jBNaSg+1Zu1mq/FEKR5eHUHLmX48/3O1cT8XBQUp0ZAkVGr1htcRz/NouzCIGz/uReG2DJz+tYZ1lTipAMswK9ZxkcYTpei6Noq2CwNxC0CWEwgE8eTOOFrPDmB2zA1Lrh7PfbkGtQesER+DMpoQ8Png93LQkvFz7tyoFUFv0qFiTx4e3xxD85sVG+4LY2Fm1IUz/9CO+UkPjnxuGxqOF205sDJmkmg8aceeE6UY651H141R9NydwKPro7Dk6VF70Irq/VbJAnie58HMcph2MMsCNBdmR13w+5Z65Y1ZJLILjSipy4YlT4/+B1O4/d5TtJwdQM0BK3a9UJyS8uNkoARuEcIHedx8txfmHAp1hws3fG1oc5smgVs4eYVarULdERvu/PQp5ifda2zjN+LehSHwPLD7paUAIlHWvumI4Iy4sQOXtTIDtupMtJ4fRP1R25qM3cOrI/A4fWjcoNoGLLPIToPftpdlwfNBUOt8d7teKkH7ZQduvN2LN/7LrpSZxbQePS0TyC8zw5ytB0XTYBPR4+ZcWFNtE6EzSGw/Uoj2yw40nlKqbgrygiCIRQl/+OsoGOTxyX88QfvHw6hszMOLv1AHtTY1K20iHufCinVcxJyjR/X+fDy8OoLGk/awpmtS4PcF8Oj6KFrPD8I5zSLbRuPlX9qOisY8qKI0chEDKZZh4hy4iRW38O0D9UdteHJnHE/ujKPu0MZ7w2jouzeJD7/1EBqtCm/8l12wVW0ujYwGgiBgrcyAtTIDR96qQm/rBLquj+LmO3249W4fiuuyUXvQirIdORH9rnmeh3vBixmHEJxNjywFaj52SfZIW3TIKqSx/agNWYW08B8rDR21MhzZfsSGmVEX7n84iK7rI+i86kDZjhzsfqkEBQmsDKYiSuAWIT2tE5gaYvDiV+qg1mz8I6YM0Tc1pzKekHPcyhv+9sOFaPmgHx1XRnDoM5URHsuLzk+EGWHL599RRhPmJ8akO+lnCMEZMfyispx9r9rx9jfa0Hl1BDtfWJL6BnxBtJ0fQOG2DBRWbiztJZdJJeVOaEEOk0kFAB2lQdMpOz75jycY7ppFcV1WIk8vKubG3ZgaYnDoZ4TrUHC2TUDg5mLCbgRF9pwoRecnStVNQZ6QNB1Wcuz3BnDhXx6ir20SO18sxqFPV6acg2Q4PIxzzTou0njSjsc3x3Dvw0Ec/HRk63mkeFk/Oq+M4N6Hg3AveJFfZsaRz1XB3pAd8wZ8SbbvhCk7+naNSGFdLoAgQBrCJ6etlRZkFdLovOKQJHAT+9nuftCPvFITTv5KQ9xnAWpJNWoOWFFzwIr5STce3RjDoxujOPdPHSBpDar2FaD2gBW5JcJvx8MsD9AEiePMiAuce6lfjjJqkV1Io6bZuiJAi1QKCwh+Cs99uRb7Xi9Hx2UH2i8P4+n9KeSXmbHrxRKU786NOuBPB5TALQICgSBu/aQPWYU0tu3N3/T1ofkvaWLgELL8XmVAQGeQKNuVi67rI9j/WllEuusHHw3D7w1iz4mVDch6k1JxixXOxYSSBRtRuC0TtqoMtJ4fwPajhdBohb9X141RuOa9eOErdZsegwo17Ms/KSHKPal1MqmAkE29f3EIN97pRVFNZspuzkSZZMUeofGQNITfcEqNx7mw5r6wnFDV7ZIDjadKo6rMKygkG9Kwdm4l6/Lhg797gNG+eRz+7LYVSbBUh2UYmEpzwz6XkW9AZVM+2i87sOflUlDGrUs+WZcPDz4exoOPh8C5/CiqycRLv1gHW3XmlismYsIo3rJ9zsWANBhAqMIn7AlCMCm5+v1uTAwsIK80dlk95/bhwr88xED7NGoOWnHsC1WhdTpRWHIN2P96Ofa+WobhRzPouj6Kh1dH0P7xMDLyDeDcPnicS47ppEGDLCuNysa8xQDNiCwrLWnVlraQ2P96OfacKMWjG6O4d3EI5/6pA+YcCjtfKEHtQSu0ZGK/p2SiBG4R8Oj6KOYnPDj9aw0RRfdiZiZdLNNZ51rLb5GG4zb0tk7gyd0J1B7cWJ/uZf1ovzSMsp05a4ZrUkYTWBcDPhhc9wapEB7O5UJGQWSZvr2vlOGdv27Dw09GsOO5YgQCQbSeHUB+mRlFEbhUaSk9CJUqLYZwhypuG1Qr1VoV9r1ehovf6kJP6wS2NW2euEkGPS0TKCi3hDKzJG2Ecyr+84VYxglzzsYuNXtOlKLz6gjunhnAC0rVTUFGkDS9ouVhYcqD9795H/NTHpz45XpUNsrLoYl1LkC/jsIAABpPleLJnXHc/2gI+18vj/lzXPMc7l8cQsdlB3xcAPYdOWg8WYqCckvMx1xNKHCLc28862LWlUmKVDcX4MbbPei44sDzX44tcJsZceGDf3gA5xSLo5+vQv0xW1LlgCoVgZK6bJTUZYN1+fDkzjj626dBWyzLKmhG0Bm6hJ2nllSj4XgRth+14en9Sdy7MIir3+/G7ff6UH/MhobjRSHfhHRGCdw2we8N4M5P+5FfZo7YhENL6UEQqrSRSrKMEyq1BlpqbY9K4bYMZBXS6Lg8vGng1nFFcC1sPGlf8xxFmwCeB+t2rSvlUAgP69q8x03EVp2Jwm0ZaD07gLrDhXhyZxzOGRZHv1AV0c2XIAiQCRp8Gm/EDdlm313VvgK0nR/ErXf7UL47F+oUc4ybHXNh2sHg8Ge3hR6jDHRCDGQ8TueaUQCroS1LVbcmpeqmICMoAw1mZhoAMDnoxPvfvI+AP4g3/vMuFG6Ttuco3vDB4OI81vWv1+xCIyp25+LBR0PY9WJx1EYrC9Me3Ds/iIfXRxH0B1HZmIc9J+3rjpfZCst73OJJuFmfqyH1GlTtzUf3nXEc+kxl1N9bb9sELn6rCxpSjTd+Y/emLQuJhqIFh8eG40XJPhUAQlBZsTsPFbvzMNo7j3sfDqLl7ADaLgyiel8Bdr1YsqY4kE6k1g4kBWm/7IBrjkPzmxURZxWEzS2dNlJJD+MEZTSG/fcTBIH6ozZMDDgx3r+w7jH8vgDufziEoppM5JetXThEgwPFWTJ6OJdr04VlOU2v2OGa9+LhJyNoOTOAnGIjSuuzI34/RSfGsTDecOKYi02+O5WKQPObFZif9KDr2taGzseDnpYJgFiSSQKLvTlx/hsFgwGwLmZdc5Ll7DlRCpWawN0P+uN6TgoKUiJeR4MPp/H2N1qhUhP41G/ukV3QBgCcxy2YMW1QcQOEUSheNoD2S8MRH3t2zIWL//oQ//ZHN9H5yQiq9uXjZ/+4GS//cn1cgjYgkRU3V0SJ0fpjRfB7g3h8K/Je/WBQGDF19n92IKuQxlu/tzflgrZUx1phwalfacAX/6QZdYeEZPT3/vQW3v/mfQw/ngXPxzZrOJVRKm4b4PX40Xp2AMW1mRHJyJYjNDXLf3MLCFLJjfpYqvcX4Mbbvei4PIx8e/g+qUc3xuBe8OKlXwz/fKJuwulGwO+Hj2MjrrgBQFF1JqwVFlz7UQ+Cfh4nf6U+KqkDRSdm8Gm8Cc3nieC7szdkw1phwZ2fPkV1c4Hkts9boadlAtYKywr7ZtJAL1ple6HRxcchjnO5AJ6PqEJOW0jUH7HhwaVhNJ6yIyNPqboppD4kbYSXK8JPv/kAmVYar/36TtAZ8pRiiZWpjdZyAMgtMcHekI17F4ew4/niNW5/y5kcdKLl7AB62yag0ahQf8yGXS+VxN1MAwC0JAWVWhP3PQPnYpBVuHmlKbfEhDy7GR1XRiKy7WddPlz454cY7JxG3SErjn6+OuVdSVOZjDwDjn2hGvteK0PnFQcefDyMd/+6DbklJux6sRgVjXkpp5aJlfT4V8SJex8OgnX50PxmRdTvJfXpUZUAhGBqoyydTq9B9f4CPLk7AZbxrXk+GBBcC/PsZtjWCYBDsgdlCHdUiL+xzTT4yyEIAntfKUPQzyOrkEb5zvDN6utB0msb9uUI5150C9NvHkQQBIHmT1XAPe/Fg4+GEnB2kSFaLlc2ruy9IxMwtsEj9r5ushEU2X2iBCo1gRal6qYgA3iex8xYLtTki7BWWvCp39wj26ANEPrbgPC96qtpOl0GzuVHx2VH2OdHe+bw/jfv4wdfv4Ohh9PYc6IUX/7aQRz5XFVCgjZAuCdTxvjL9rkoWhHqjxZidtSF0Z65DV837WDwH39+F8OPZnDsZ6vx3JdrlaBNIvRGHZpOl+Hnvn4Qz32pRnCA/eeH+O4f3sC9Dwfh9fg3P0iKo/xSNoAy6lB3yBqTS1AipEqJQpBKbvwd1B+zIeALouv6WinZk7sTWJhi0XiydN0slHh8peIWHWIAFclivJyi2kw0nbbj2BeqonZKJGljQmaExRuWEdw4IzXDKazMQGlDNlrPCQmdVGBJJrky+E7EoHR2nTEh60FbSDQcs+HRzbGo5EQKCokmGAji8ve6MdJDI8B14YWft4PUy1ugtDSPdfP9TH6ZGcV1Wbj34SB8XmEGF8/zIcnoj/+qFeP9C9j/ejl+7usHceDNirjNftuIRKg/Ih23AwCVTfkgDZp1A15AuGf/8C9b4OcCePM39qD+qE2qU1VYhkarRt3hQnzhq/vxyv+9A5ZcPa79sAf/+nvXcO1HPXDOsMk+xZiR950ozux4LvZGTNJAY25sRMKzSR4s40R++cZzXbJtRhRuy0DHlWHserE4FAzwQR6t5waQaaVRtoG5ixh4eJTALSpCcr8IxgEshyCImF3DqARZzccbzh1Z78Jymt+owPe/dhut5wYkn3UULTzPo7dlArZtGWuctBIxSzK0EYygx01k/xvlmBx04qN/7YLepEVJXeS9lQoKicDnDeD8/+pE/4MplNYBj6+dgY97M9mntWVC81gjvF6bTtnx9jda8fDqCExZFFrO9mNiwAn6/2fvveMlKet8/09Vh6quqj5xcp5hAgxMHgyAiAlBRMa4uhjWsOwqogvu6qb7u9e7e+8q6gZQUTfgXrOCAREQRQyEZZ1hEsMME5icZ87MnKrqqupUvz+qq7pP7u7TVfU83d/369WvTqe7n9Nd9TzPN32+PRKuevsSLL9qVuwS7LKWDdXZWyoWUHScutrtAEAqncDFL5uJ7b85gtxgfogxWy67eOYnL+LZnx/EjEVduO6WFVxHcHlBEAUsWDkFC1ZOwamDg9jyi0PY+thhbHvsMBZfPg2rXzsPU+fyJYhHEbeQGC4jzDMT1bj5XPbK2Rg8Y+PQ8wPBYwe2n8HAMdOLto0T2altpknUj78xb0ScZLJImpcqyXvRr5cC09j3NmWOhqUvmY5tjx/B2WPxGq8Dx0ycO5EbVZJciqDfnhWkXtW/6CVTCVz/4ZXonanika8+h1MHxxY0IoiosfQ8fvJPm3Fg+xlc/c6lWH6Vd2y3g9BYkNpc5/k6a0kPZi3pwRM/2IOHv7odtlnANTcvw3v+7uVY9Zq5sRttAEJPlfTXV6mBjJZLr56FcsnFzqeqjnvbLODBL27Fsz8/iEtfMQsbbuc77ZZXps3vwrUfugzv/t8vw4pr5mD/ljN47Os7udvLkOEWEl4DXP4Nt0LeQbGQr2uyX7R6KpSuNJ77jadG5bouNj1yENl+GUvWj9/vRkwkPGO3DWTmo6QRgY1WIasaSsUiinknss8MA9s0g4bijfDSNy1COpPEjz7/LI6+cC6EkdXH3k2nIAjAojWjGG6VmscwI6PVVMnGUsmlTBI33rYKkpr0emKdbo9+l0Rj7HzqOO795BP4xb07cGD7GZSK5VjHc+F0DvffuQlnjhi4/k9WYMU1c4JMhnZYy4MIeQPOqivfthhzL/GaZt/86Zfh0lfMZqoWy+v/Gp6z119f6424AUDvDBWzl/Vgx++OoVx2ceaIgR/8w+9xdPc5XHPzMlxz88VMfYedSNeUDK56xxK87x+uwOs+sDzWfnnNQEdPSEiKioJtoVwqxT2USeGLhdRTx5JIilh+1SwceO4sBs9YOLr7PE7uH8Taa+dBrEPNR9aygRefqI9YIm5tsplpJuIGAF39GbztU+ugdEt44K4tsdRrua6LPRtPYvay3lFrS/zU47DFSQRBhKQ0rhCp9kh408dWo1x28cBdW5EbzIcwQoJVdj19HL/6xk7IWgoHt5/Fz760Dfd+8gk8/o2dOLxrAOVytB7wkwcGcf+dm2DnCrjpz9Zg0WqvZjSK8ygqbEOHpKgQE/VHyqbN78KbPr4GS18yo641PGrCTpVsJuIGAJe+Yjb0szae+P4e3H/nRpQKZbz5jrW49BVUz8YSkpJC/+zo9k6tgmrcQsL35DtWjuuG0o3WsVz6ilnY9MhB7PjdUZw6qCPTlcbFEzTm9slo2baQmY+SWCJuvgKoaUDr47dGyTaNhtQ4a+nqz+Ctf7EWD391O3557/MYPGNh/RsWROa5O3PEwIVTFta8bt6oz/vGdZgiMrYx6PV3rFPcZTi9M1S88dZV+Mk/bcaDX9yKDXesGVd6nGgPXnjmBB77fzsxZ1kvbvjISgiigMM7B7Bn40ns2XgKzz95HJmuNBavm4Yl66djxsKuhgWUGuHA9jP4+b8+h0w2jRtvW4XeGdW5tF2cVEBFHbqBelQekDUNectCqVhEItn6uaNaQ97YOrFo9VRkutLY/usjmHlRN15/y2Uj6pAJollolQyJQI7bNLk23IK8eLW+/0HrlbFw1RRs+/VRFJ0SXv7mi5BM1efhC9t71o44OROJZBLJdHSLQtUo4NvIdkyzYTXOWiQlhRtvW43Hv7EL//3T/dDP2njlzcsi6RWzd9MpCKIQRAaGk0ynkUilQo+41dsKYCxmLOrG6//4Mjz0le145GvP4YaPrEQiyZ5nfyzOn8rhN99+AUsun47lV86KezjMs/u/T+Cxrz+P2Ut78YaPrESy0g9xwYopWLBiCor5Eg5sP4u9G0/i+SeOYfvjR6D1SViybjqWXD4dU+ZqLXWOPP/kMfz6Wy9gyhwNN9y6csTmOgp11qiwDL3udZwXZLWaEq50t75xdaDa3GBmRiIp4uo/WIqBYwbWXb+AqzmNYB8y3EKi6qnje8L388frVaICgBWvnI0XN5+GpCQbkrqVtSzOnxjZToAYG8fw0v2izNGWa5wSvFIsFFDMOw2rcQ4nkRTxmj+6BNl+GRsfOgDjnI3rblmBdIjS4a7rYu/Gk5izrAeZ7NgS3JKiwgmxZtQ29JY4pRasnIJrbl6Gx7+xC7/6xk689n3LQ42wtIrj+y7goXu2wTELOLLrHM6fyOHlb76Ii7HHwZ6NJ/HLe5/HrCU9uOEjK0dtYp9MJ7B43TQsXjcNeauI/dvOYM/Gk9j62GFs/sUhdE/LYMn66Viyfjr6ZjV/7rqui98/uB+//9kBzFveh9ffctmo0d5kWoKYSLZNqmQj6zgP+LX3dkiGm5+x0ExGy+J104BRhKMIYrKQ4RYSft2Hk+O78N5uUIkKAGYv68X8y/ox95K+hjawFHFrHDtnTtr4aJRAsZBjp0SzntTR8FsrdE2R8etvvoAffn4T3vjRVdB6w2lEe/qQ7vVFvH7BuH8nqVqoyraWoSPbP3aLj0ZYfuUs5C44eOaB/VC7pdhbLUzEno0n8djXd0Lrk/CWP1+Lbb86gs2/OIQLpy289gPLRzVKOpm9m07hF//xPGYu7sENt66qS5EwnUli2UtnYNlLZ8A2C3hx82ns2XgSmx4+gI0PHUD/bBWL10/HkvXT0D21/jrLUqmM33zrBex86jgufvkMXPPui8eMkguC4PVk5dhJ5WPrOnqm11e2wAuB4RbSvqGV6wRBtAoy3EIiSJXkXEY4kPxuwFMnCALe+NFVDX+WrGVh50yUyyWIIm186sExjcgXFf/Y5rkJd1C7MIlUyeFccsUsaL0yHvnqdtz3mY244aOrQukPs3fTKYiigEWrRk+T9Am7356t65g2f2HL3m/d9Qtgns9j86OHoHZLWPWauS1771bhui42P3oIT/9oH2Yu7sYb/nQlZC2Fq9+1FD3TFTxx3x78+AvP4g0fGZl216ns23wKj/77DsxY1IUbbl3ZlIy8rKaw/KpZWH7VLJgXHOx79jT2bjyJZ37yIp75yYuYNj+LJZdPx+J108Z1mOTtIn7+rztwaMdZrH/DArzkxoUTZivIqtoWETfLGGzIAcsDQb11SJkFtmkgkUohmY6+uThBjAUZbiHRLkXNtmkgmUojFUENVUbTANf16gInWTvTKTimEfliXFtXwCuBGmeLo5VzL+nDW/5iHR784lb86PPP4rpbLsO8S1sn4OK6LvZuOoU5l/RC1lLj/q2kqqHW5rR6IygIAl7xzqXI6Xk88YM9ULrSWHL59Ja9/2Qplcr47Xd24/knjmHJ5dPx6vdeHNTvCoKAVa+Zi66pGTz67zs8w/3WVZgyp7M99S9uOY1H/3UHpi/owhs/uqol4jNqt4SVr5qDla+aA33Axp6NJ7F34yk8ed9ePHnfXsxc3I2ll0/HojXThiiu5gbzePCLW3HmsI5rbl5Wt8KfFLIDJArK5VJlXW03wy3kiFvOpGgbwRxUMRkSUTTAjQJLH4xMicoXOqB0yfpxcmZTkvaTQUwkkJIzXBfsO4EaZ+u/u/7ZGt72qfXonpbBg1/ahuefODbxi+rk1AEd+lkbi9dNbNCE2UuymM+j6Dgtd7CIooDXfWA5Zi7uxi+//jyO7Bpo6fs3S94q4meV33Ld9fPxuvcvH1V0aeHKKXjLJ9bCdYEffm4TDmw/E8No2WD/Nk+tcer8LG68rTVG23CyfTLWXjsf7/jry3Hzp1+Gl9y4ELZRwG++sxtf/8sn8cBdW7DzqWMVuf+NOHfCxBs+vLIhWfawU46jwI9ItV/ELWTDzTAiL0UgiIkgwy0k0pkMAL7TyQBvwo9qsvfTHnwlS2JibMNoqon0ZJFVjetosr8RC6uNgtoj4c2fWIu5l/Ti8W/uwn/9eB/cFvSm2rvpJMSEgIWrJq4tk0JM8bKMSgp1CHNDMpXAGz68Ej3TFTz0le04fTje+UAfsPHDz2/C0V3n8Kr3XIyX3TS+AMnUednAcH/oy9uw7fEjEY6WDQ5sP4NHvrodU+ZmcePHVocq1uPTM13B5TcsxLv+50vxzv/xEqy9dh4unMrhV/9vF+77zEbk7RI23L4WC1Y2VpcZtshPFPiGG88K16MhKQogCLDCSpXMmS1NpyeIVkCpkiEhigmkMwry3HvqBiOb7H2pYl/Jkhgf13VjibgB4afhhY2/EQszDSYtJ3HDR1biN9/djU2PHMTgWRuvee8lSKSa85e5ZS9Ncu7yPsjq+GmSgBcpcEwDruu2XHU02AiGFI2X1RRuvG0V7r9zEx68eyve+sl16JqSCeWzxuP0IR0Pfmkrik4Jb7xtFeZe0lfX67Rez3D/xX88j999bzfOn8rhqrcvgdgBipMHnzuLh7+6HVPmaHjTx1ZBisBoq0UQBPTP1tA/W8NLb1qEUwd1HN19DhetmdqQiIlPmA6QqLBDdLTEiSgmIClKaKmsjmlA6eoO5b0Jolko4hYi7THhG5GlSvqbwLAKjduNgmOjXCrFksohqxrXwjt2iKmStYgJEdf84TK8bMMi7Pn9STxw1xbYZqGp9zp5YBDGOQdL6pSYllUNpWIRxUK+qc8bD9sXLdLCq0XVemXceNtqlIpl/PTurbCM1v8f43Fg2xn88AvPQkwIeMtfrKvbaPNJy0lc/6crsOq1c7H98SN46J5tyNvFkEbLBod2nMXDX9mO/lkabvzYakjKxA6GMBEEAdMXdGHttfObMtqAcFOOoyJIlWyzGjcgXDVqx4zHMUoQ40GGW4jIisp9qqSlR6dEFeSrVzaFxPgEAhsxpHJIqsZ1+pCTM5FMS0imwt9YCoKAddctwLUfvBQn9l/A/XduwoXTVsPvs3fjKYhJAQsmUJP0CVMgyTL8NiHhHnt9s1Tc8JGV0Ads/OxL21BwSqF+ns/2X3uGVu90BW/71Hr0z27u/xRFAVe9bQle+a6lOLRjAD/8/LPQB+wWj5YNDu8cwENf2Y7emQre9PHVdUWFeUBWNRQLeRTz0ToOWkmgDt1mETfAy9QJy3CzTYMMN4I5yHALkbSich2VcF0XtmFEliopqWqo+ertRhA1UqJfWGSVb6dEHLWBSy6fjps+vgaWnsf9d27Eyf31Oyjcsou9z57CvOX9daeeVfvttf538vs7RqH+OnNxD6794KU4dWAQP//X51AqlUP7rHLZxRM/2IPffnc35q+Ygjd/Ym1LZP0ve+UcvPHWlRg8Y+G+z27EqYPt5Zw6smsAP/vyNvRMU3DTx9e0jdEG1DhAOM6eqda4tZ9as6xpoWTpuBWFa1KVJFiDDLcQ8VIl+W3AXbAtlEvFyLx0opjwopSkKlkXVWXE6FMlJc5TJZ1cPJ7UWUt68NZPrkNKSuDH//gsXtxyuq7XHX/xAszzDhbXmSYJVFsdhFGL2Ex/x8mwaPVUXP2uZQsIvTgAACAASURBVDj43Fn8+lsvwHUnL/QynEK+hEe+uh1bHzuMla+eg+v/dEVTPcfGYt6l/XjrX6yDmBDwo8/X/9uzztEXzuFnX9qG7qkZ3PRnqydsU8Eb7aAQbRuDEATRE/NoM2QtG0pdfN6y4LrlWNZXghgPMtxCROY8Nz6OvPgw89XbDX8jEYdHUFJU5C0L5VI0qWutxokxBaZ3hoq3fnI9+mZrePir27H1V4cnfM3eTaeQSIp1qUn6+P9fGAa2ZehIpqVI+jv6XHb1bFx+wwLseuo4nnngxZa+d24wjx9/4Vkc2HYGV71jCV7xjqWhCIn4rSL8337zo4dCMUKj4tiec3jwS1uRnZLBTX+2Bpls+zUqDjNyHRWWrkPSNAhi+235ZC0bSpaOP29SxI1gjfY7ixmC96hEHHnxcpYMt3rxDes4PIJ+bROvXmjbNGNpo+CjdKWx4Y41WLhyCp74/h488f09KI/RLqBcdrHv2VOYf1l/Q72wwk6VjEPo4PI3LsTyq2Zh08MHsf3XrZHZHzhm4r7PbMTAcdMTE3n13Ja871io3RLefMcaXLRmGp764V78+tsvhJr+GRbH9p7HT7+4Ddk+GRtuXzOk2XU74aei89yE2zb0tmsF4CNX6q3dcmvPoTjXV4IYDzLcQsRPlWz1hBIVvgBBlBM+RdzqJ86Im/+ZvLYEiDPi5pNKJ3Ddn6zAylfPwdZfHcbPv/YcCvmREczje88jdyHfUJokEK44iW3GsxEUBAGvfNdSLFg5Bb/93m7s3XRqUu93ZNcA7v/cJpSKZbz5E2uxsE7hl8mSTCfw+g9dirXXzcfzvzuGB+/eCifXnNpoHBzfdwEP3r0VWo+Em9rYaAMQOHh4bsJtGXosIlZRIGsaXLeMvN244NN4xLm+EsR4kOEWIlJGAVwXeZtPFTE7UI6L0HBTtcBgJMYn8AjG0A6A9/Qh2zRi+d6GI4oCXvGOpbjq7Uvw4tbT+Mk/bUZucKh63d5Np5BMiZi/or+h9w5TVMHS9dB6uE2EmBBx7YcuxYyF3fjFvTtwdPe5pt5n19PH8dO7tkLrlfC2v1yPafOjFW4QRAEv33ARXv3ei3Fs93nc/7lnMXimtZvPMDjx4gX89O4tULrT2HD7mpaIt7BMmA6QqLANPRIhoTgI1KhbvG+oin/Fv04QRC1kuIVImDUmURClcpxPJttFEbc6cXIm0pkMxETrBBTqReI44uaWy3ByOaY80KteMxfX/8kKnD1i4P47N+LcCW+TGKRJrmgsTRIAkuk0kql0KL+RrQ9CVuNLvUqlE7jh1pXonpLBQ/dsx9mj9f+PruvimQdexGP/uROzlvbgLX+xDtk+OcTRjs8lV8zCjR9fjdwFB/d9diNOvHghtrFMxMn9g/jpXVugZNPYcPtaqD3tbbQB7SJOordt5KhquLV2nouz3Q5BjAcZbiHCfVQiol5NtciaBsc0uRW9iBLHNGJpBQBUFQt5rPtwrBzgusxtZBatnooNd6xFwSnh/s9twrE953Fs9zlYegGL101v6j29dO1w+rjF3cxXVlO48WOrkUqL+OldW+rqj1YqlPHLe5/HxocO4JIrZ+KNt62qu71CmMxZ1uupjcpJ/PgfN2PPxpNxD2kEpw4O4oG7tkDWUthwxxpove1vtAFAMi0hkUxyOdf52IYOuW0jbt483upMHSfGdjsEMR5kuIUI7ykWlqEjJWeQSEYn7xx4zzheJKMiToENyRcn4fDY9sfMYgrM9IVdeOsn1yOjpfGTf9mMp3+0D8m0iPmXNZYm6SOFoGzr9XdkI/Uq2yfjxo+tRiFfxk/v2gLbGLtOzDYLeOCuLdj93yfxsg2L8Kp3X4xEgp0lsHeGird9ah2mzc/i0X/bgY0P7WdGcfL0IR0P/MsWyGoSG+5YC603vghl1AiCUBEa42+uA4BSsYC8ZbWtOEkmtFRJExCEtmyhQPANO6tWG+JvDHktavY2Z9FO9pmQ0h7akTgFNngWJwlqFxhNgememsFbP7kOMxZ249RBHQtWTmm6n5iktX7D6eRMuOVypLWv49E/W8MbPrwCg2ds/OzLW0cVeLlwOof779yEE/sv4NoPXop11y2AILRe7n+yZLQ0bvqzNVj6kul45oH9eOw/d6JUiFfc6vRhHT/5581Iy0ncdPuaWNNK40JSVG8jzyFBWx9GztdWE16qpAFJUdqyhQLBN3REhoifKpnn2HCLuo6lOgkPRvq5PBKn4ZZMSxATfKYPBbULDEbcfGQ1hTd9bDVetmERXnrjoubfR1Fb/hvFUfs6EbOX9uJ1H1iOE/sH8ei/7UC5Rl7/xIsXcN9nN8E2Crjpz9ZgyeXNpZ1GRSIl4rXvX47L37gQL/zXCTwwQSQxTM4cMfDAP29BSk5gwx1r0NWfiWUccRNWynEUBCUPMac2h0WgJdDieS7OUgSCGA8y3EIkiLhx6qmLo47F/zyKuE2MnYsvVVIQBMiaxmXELahdYKzGbTiJlIh11y1Az/TmU3XCSPGKQ222Hi5aOw1X/8FSHNh2Br/5zm64rou9m07hx/+4GVImibd+ch1mLe6Je5h1IQgCXvLGhXjt+5fjxP4LuO/OjTh/MhfpGM4eNfCTf96MZFrEhtvXomtKZxptgJ9yzN9cB8TTjzVKkqkUkpLU8ho32zSYq4MmCACIvyq7janKcfM54du6jmx/NH2NfMKS9m1HnJgl7XlNH/KNzU5YlCVFbbkTJOjvyKAHf8U1c2BecLDp4YPQz1o4vPMcZl7Ujes/vAIZjb9eY8teOgPZfhkPf2U77rtzI9ZeOx/pTBKptIhkOlG5iMF1athjothcOujZY57RlkiKuOn2Neie2rlGG+A5QPQzp+MeRlP453+71rgB4fR/tU2Tmm8TTEKGW4gkkkmkJJlLAQegUuMW8WTvG26WTobbeJRLJeQtK9aokaxqXHqheYm4tQI/xct13ZbVdNmMe/Bf+qZFyF3IY+dTx7Fk/TS8+n2XIJmKvmVGq5i1uAdv+9Q6PHTPdjz9o30NvTaRFJGUhhl0qYqRJw018nxjMJEUseWXhyCIAjbcvgY900icQVb4TZW0DLbP11aQUbVQatz6Zs1p6XsSRCsgwy1kJEWBk4s2xaUVuOUybMOIfLKXFRUQBNgmGW7j4W8i4kqVBDyjgMfIqG2aEAQR6Uz7RxEkRUW5VELRcZCSWyMqYTGaKukjCAKuuXkZll81C9MXdEFoMurEEt1TFbzzb1+CvF1EMV9GIV9CMV9GMV+qXPzHSqM8P/Q5/zWWUfBuOyUUC97flIueiqXWK+FNH189qTTddkJSVS7TwoGaiBuDEfJWEUbEzashp4gbwR5kuIWMV2PC34Tv5HJw3XLkk70gipBVjSJuExBI2scYNZJUDRdOnYjt85vFyXkLMouqgq0mUP/MGa0z3HQdqNQ4soqYEDFjUXfcw2gpgihAUlKQQrSlyqUyioUyEimRqVYJcSMpKkqFAor5PJJpvlJubX0QYiKBlNy+jipZy2Lg2JGWvqedMzsiK4PgD5qZQyaMPkpREKcAgaxpXEZyosRmIN1PDiE9JQpso3OKzn2PcSvnINsYhKyoEEV+0w+J0RETItJykoy2YQTKhRymS/qZM+3sqJJanLZfKhZQdBymlYeJzoVm55DhVUY4zrz4jNZFhtsEBJL2cadKmgYzTYLrxcl1TtF5IJDUUsPNaFtpcYIYDX++4DFd0jIGmWrdEQaes7d1v02Q0cJwVgHRuZDhFjISp0XNcebFU8RtYliJuLnlMgqOHdsYmsGOsf9d1AQRtxbOQZY+iIzW3htBgqhFDsEBEhW2rjOd1twKZC2LYiGPQt5pyfsFysMUcSMYhAy3kOE2VTJG5bgwCo3bDb9uMs6Uv8ALzVm6pGOaHbMg+w1kW5lGZMfQ35Eg4iQMB0hU2IYOuc0dLZkWtxGiiBvBMmS4hUytHDdPWJXNeCyGWzbLnTEQNVVxkvgMEJnTug/HNDpmQfY97XZLI246s4qSBBEGYThAosIyOiHiVpnnWrRvCDJalPb+3gg+IcMtZGrluHnC9mvcYojoyGoWTs5EuVSK/LN5wTYNCKKIlNQapcBmCAr2OTOybbODxEkUT4Kw1eIk7dzMlyCGw3fEzeiAGrdWR9ziz2ghiLEgwy1kfHEAm7OWALbhSaaLieiV4/y6Oh4LwaPCMU3IqharUlggNc/R71TM51EqFILzst1JJFNISlLLfqNSsYC8ZVGqJNFRVMVJ+DLcCnkHxbzT9gZIqw03m4GMFoIYCzLcQsY/8fOcNeG29MHY0qFaPQm3IzYDzUF5lMgOis7bPHWoFrmFdbaBaFGb18wQRC3JVBqJZJKruQ6orqFtH3FrsRORIm4Ey5DhFjK+CAJvnjrb0GNLh/INN2rCPTZOzox9UeFRnCSoDeyQiBtQ6XHUooh/0N+RIm5EByEIQst7hUWBrXfG+RpGjVsileKu2TrRGZDhFjLVqARnE74RnwBBqxWi2hHHiF/SPqif4ujYtjvQk9pKZVurojZLETei0+BRIdp3fspqextuKTkDMZFoXY0bA45RghgLMtxCJihq5m3Cj9Fwo1TJibFzZuyGmygmICkqVzVuvpEZ93cXJb6ybSuw/IhbB6WaEgTgOXu4S5U0/VTJ9jbcBEFoaRshxzA6KiuD4Asy3ELGP/kdzmrc4oy4keE2MY5pMNGLTFJVrlQl/bF2lOHWyho3vTNqZghiOJLKX8QtSJXsABVYWdValyqZMzumZQzBH2S4hUxguHEUlSiXSnBMMzYvnaQoEASRDLcxcF2XmV5kkqq1tEdY2HSiOEkrfyM/VbLda2YIYjiSonI11wE1EfIOOF9bGnFjxDFKEKNBhlvIJNNpJFIprlIsqpvbeLzqgihC0jQSJxmDYiGPUrHIRCqHp1jIj1OiE8VJZNX7jVzXnfR72YaORDIZa/9AgogDSeVrrgO88zWZSiOVluIeSujImtZCVcn4SxEIYizIcIsA3oqaAwnhGKMSGU2jiNsY+Ol+MgM9ZjylNY6ObdNASpKRSCbjHkpkSIoKt1xGwbEn/V6WrkPOdsXaP5Ag4kDiscbN0Dsi2ga0OFXSjF/8iyDGggy3CJCU1okDREFV8ju+OhZZy3IlehEl/rHEwsLSSi9nFDg5M/b+d1ETKNu2wMCOs00IQcSJpKgoFQoo5vNxD6VuLD2+WvWoaVWqpFeKQKqSBLuQ4RYBrVR1i4JAQjjGiJusZYN6GmIovleRhRx83lQlbcPouAVZVltXZ9tJHnyCqCU4jzhayzvJ0SJrWeStHErF4qTeJ29ZcN1yxzn4CH4gwy0C+E2VjC/iltGyXDV2jpIg4saAwIasaig6DkrFQtxDqYuOjLgplea0LTDcLH2w7XtCEcRo+HWxPK1LneRo8R3NkzWs/ZYxnebgI/iBDLcI4E55z4hfQriVClHthr8B9zfkccJbn8JOrF2QWhgpsA297XtCEcRoBCnHOX4MN0sf7KhUSWDybYTsoGVMZzn4CH4gwy0CJEXhSo3K0nUIgghJUWIbQ6vSHtoRhyFJe98raXNiuHWizHOrjGvXdQNxEoLoNKqtffiY61zXhW0YnZMq6a9FkzTcfAcXRdwIViHDLQIkRUWeowbctqFD0jQIYnyHh5/ewZPBGxXViFv8BkhV+IKP38kxO6+xapDiNckNZ8G2UC4VO2YjSBC1+A4QXrJn/PO14yJuk1yLWFpfCWI0yHCLAFnVUCzkuVGjshgoaPYnYerlNhLHNJmRtJfU1tVPhU25XIKT6zy1sCBSMMkUr0AUh1IliQ5EbqE6axR02vnqZ6BMtgbR/31ZyGghiNEgwy0CqhsnXiZ8PfZJK9OitId2hCWBDZmjiFs+ZwFgozYwSvyG2ZPdcPoqr3GKFhFEXFRTJdmf64Dq+dpxEbfJpkr6EbcOc/AR/ECGWwS0UhwgCmxdRybmOha/jsY2yXAbDkuS9kH6EAdeaJuh2sCoaUVLEivo79gZG0GCqCWZTiORSvGzjlciT3Fnz0RFsBZNVpzENAFBgJSJr8afIMaDDLcI4C7iZsbftJNSJceGIm7N4XRw7UIrWpLYQcStMzaCBDEcnlr7WEblfO0QMSFRTEBS1RakShqQFCXWGn+CGA86MiOANzUqS2fBcKNUybGwTYMZ48P3QvNQ4xZE3BiJVkaJpGqTrnGzGGgTQhBxwlNrH1vvvPO1FW2EPMOt89YIgh/IcIsAnlIlS8UCCrYVu1ddUlQIoshVs9OocEy2BDZkVePi2K7WLrBh9EaJrKqTTmftxI0gQdQiKyoX2QVAbT9WdtaKsJFVrSWqkiytrwQxHDLcIoCnJsWBElXMmzNBELxJuJLuQVRxGGsiLakaHA4MbN9wYem7iwpJ1Sa94bSMQaQzChNqpgQRB62oFY0Ky9CRkjNIJFNxDyUyWhFxs012ShEIYjTIcIsAnmrcbIYECORsFywODIIocctlOFaOKeNDUlUuUiVZalweNS2pcTMMZBiYFwgiLniqcbMNvePOV8/ZO/kaN4q4ESxDhlsEpCQZgihyYbixJCEsaxrVuA3DyeUA14XMkEeQm1TJnAlBFJGS5LiHEjmyqsLJ5eCWy02/h60PQqZWAEQHI2t8zHVApa2PGv86HiUtq3FjaH0liOGQ4RYBgiB4Rc0ceOp8AYK4a9z8MdikKjkEX2CCqYibwkfEzW+jIAhC3EOJHElR4bpl5G276fewGOjvSBBxIlVq3FzXjXsoE2IZOhOZM1HiGW7G5BxUOZOp9ZUghkOGW0TwUtRsM6QcJ2tZ6uM2jGqdFjseQVnTuEgfYqmNQtT4G5HJKEuy0N+RIOJEUjWUikUUC/m4hzIhNgPq0FEja1rFQWU19fpSsYCi40BmRLWZIEaDDLeI4KWo2Y9wsZAbL2tZ6uM2DIdBSXtZ9Qy3yXg5o6CT1cJaIZBkGYMdtxEkiFp4au1jGToTmTNR4s/vzda5+b+rRJkFBMOQ4RYRkqJ49UmMYxs6xEQSKTkT91AgaxoKtoVSsRD3UJghWFgY8ghW0/Ca83JGBWtqnFEy2Q1nuVSCY5pMOHQIIi54UYh2y2U4HSgm5DuWmq1zC3p9MrS+EsRwyHCLCEmZvBx3FPh1LCzUAWUqQgjUy60Ki02kfe8k65sZT+aZne8tSgJPdJNR/+C4I3ESooORA4VottckJ5eD65Y7LkLu1+BSxI1oZ8hwiwhuUiUNdupYqpMwpUv6VJtIs7OwyErld2LcMeHJPHemJ7UacWvuN/LPwU7z4BNELf68y/pcx1KtepQEEbcma+P931VS2FlfCWI4ZLhFBC/9X7yCZjYmLX8StshwC7BNE4IgIi2zI2kfCF8wvJlxXbezUyX9qGiTziO/1rTTamYIohZeUiUtg522PlEy2VRJFmvICWI4ZLhFhKSoKDg2yqVS3EMZF9vQmUmH8iN/lCpZxcl5PWYEkZ1TN4iMMmy4FfMOSsVixy7IUkYB0PyG0+7QjSBB1MKLOIm/ZnZahHyy4iQsqjYTxHDY2f21OYGnjvF0SZZ6NQUGQaUpOOEtSKwtKv5mhmXDjUVRlygREwmkM5mmfyM/4iYzkkZNEHEQGG6Mr+P+mtlpjpZkOo2kJDWdpUMRN4IHyHCLCJ48dezUuE0u7aEdcXImc4uKzIE4SVVcg63vLko8gaQmI26VjWCnefAJopZkOo1kKs20kwoALMOf7zrvfPXa0zQbcTOQSKWQTKdbPCqCaB1kuEVEtQEuu5vbQt5BMe8wYxikMwoEUaQatxps02AuapSWM4AgMF3j1ukRN8AXSGoy4mbolaid0uJREQRf8CA0Vk1tZmMtjxJZyzZf48agY5QghkOGW0RISqXGhOEJv9p8m42ImyAIk5qE2xHHZG9hEUQRsqIG9QEswmIbhaiZjECSV/uaZaJNCEHECQ9CY5auQ1JViGIi7qFEjqxpzbcDMNhzjBLEcMhwiwgeUiWrEsLsbG4zWpbESWpwciZzNW5AxQvNdMStIvPM0LEdNZKqNt/HTdc7Mu2KIIbDR8RND/qgdhqy2ryz186ZHb1GEHzQsOEmCEK3IAgPC4LwqCAIPxIEIS0Iwr8LgvC0IAh/W/N3Ix7rZKoNcNnd3AYCBAxN+F7EjcRJfByDTUl7SdWYrvuwKVUS8iQiBZahU30bQcCb61h2UgF+hJy9dSIKJpUqaRpBk3WCYJVmIm43A/hH13WvBXACwDsBJFzXfTmARYIgLBEE4S3DH2vdkPmEh/4vftNKljZosqYFhdadTjGfR7GQZzLdzysIZ/fYJrWwyoazSceRrQ9SxI0gUEmV5CDi1qkKsJNKlTRNJh2jBFFLw4ab67pfdl33F5W7UwG8G8D3K/cfBXAVgGtGeWwEgiDcIgjCRkEQNp4+fbrRoXBFIODA8IRvBxE3djZomWwX1bhV8I8dFqNGkqoyHXFzcgZScgZiovNqPny8FK8c3HK54ddaBqVKEgQAyCrb9bxA5XztUANEVjUUC3kU8k7Dr7VNNjNaCKKWpmvcBEF4OYBeAIcBHK08PABgOgB1lMdG4Lru11zXXe+67vqpU6c2OxQuEEQRUkZh2nDz1RtlxiJuvkHZ6dgM12nJqsb0sW0b7Im6RI2kqIDrIm9bDb/W1nVmRIsIIk58cRLXdeMeypjYRueer76DyWkw6ua6LpPiXwQxnKYMN0EQ+gDcDeADAAwAmcpTWuU9R3us4/EEHFje3OpIptJIpaW4hxIgq1kUHBvFQiHuocROkO7HZMRNa3ihjBInx17j8qjxNySNzkHe+ZeniBtBwJvryqUiik1EdKKgXCp5BgiDDr4oaLb/a96y4Lrljl8nCPZpRpwkDeAHAP7Kdd2DADahmgq5CsCBMR7reFjPjffy4tnanPl5+qwXg0dB0IuMQY+gn55SzOfjHsqo2KbR8Z5Uf0PSaEqrXy/CUu0rQcRFsw6QqAhanzAkMhYlvsHaaJ2bX//b6esEwT7JJl7zQQBrAfyNIAh/A+BeAO8RBGEWgOsBvAyAC+B3wx7reFiPuFkMSn77k7ClD0Lt6Y15NPESpEoy6BGsbTCfTKdjHs1IHMNA17QZcQ8jViTF33A2tqGxdE/VtVPlxQmilkBoLGdC6+uPeTQj8SNNnepo8fcwltlYxM039FhcXwmilmbESe5xXbfXdd1rKpf/hCdG8l8AXuW67gXXdQeHP9bKQfMKDxG3DHOGW3NpD+2Ib/Sz6BEMojmMpkvaORNyhy/IwW/U4BxkM1j7ShBx4YtDsSpQYjEoMhYlmSb3DP7ejMX1lSBqaSbiNgLXdc+hqiI55mOdDg+GW9+sOXEPYwj+JGyR4ca0qmSQPsRon0KH1MICw7XRqH+nbwQJopZqxI3NuS6IuHXo+dpsqmSQ0cLg+koQtZBoSISwnyo5yJxXnSJuVWzTQDKVZjIVseqFZm8zUy6VkLesjl+Qq6mSjUbc/FRJtuYGgoiDZs+jqAgi5B16vqbkDARRbDglPMho6VBRF4IfyHCLEEnR4FjN9VEKG9d1YRsGc5szP0+f1RS8KHFMg8lWAEB1sWNRWTJIgWH0u4uKtOIJ/TYaKQgibh0qL04QtchNivxERaenNguCAFnLNp4qGdSQd/Y6QbAPGW4RIilK032UwqZgWyiXisx56fymyXZFIKGTsU2D2aiRnyrZaP1UFARqnIx+d1EhigmkM0pTEbeUJCOZSoU0MoLgh7TSXMpxVFi6DkHw+sZ2KrKWhdVwqqQJCEJHf28EH5DhFiFSkzUmUeBHtFjz0lW9Z2x6N6OE5eagwbHN4O9Ulcdm87uLEkltvM7WNgzm5gWCiItkKoVkWmK2Xt02dMiaBkHs3O2drGlNRdwkReno743gAzpCI0Su5MazmGLhS36zFnED0FTaQztim+w2kU4kU0hKEtsRN0aN3iiRFbVhNTxLH6RWAARRg1evzt46DnhCXp2e1pxpMlXSr18kCJYhwy1Cavu/sEbQZJdRw41UJb3jhtWIG+AZBSxuZoKIW4enSgKe8dpwjVvFg08QhIeksCs0ZuuDHX++yqrWlKoky+srQfiQ4RYhEsO58ZbBcsSt8bSHdsQx2I24ARWjgMFjOyg67/DNDNDcb2Tr5MEniFokVWUyuwAAkyJjUSNpWuOqkjmT6fWVIHzIcIuQwHBjcMIPIm4MbtAyWlfH17i55TKcXI5pj6CsaUymAVcjbux+d1Ehq2rDv5Fl6B2/ESSIWmSGI26WMcikAzZKZDULJ2eiXCrV/RrboIgbwQdkuEUI06mSQY0bexOXrGlBRLBTyds2XLfMtDKipDRuFESBYxoQE0kkJSnuocROoylebrkMxzCCthwEQTSXchwVNp2v1f6vDaxHDsM15ARRCxluEcJ2qqSOlJxBIsme5LesZVF0HBTz+biHEhs8pPvJrKZKVlJgBEGIeyixI6kq8lYO5XJ9nmgnl4PrliGTOAlBBLBa41YqFlCwLchqZxtumco62Uimjp0zScCK4AIy3CJETCSQkjNMeupshgUIqk24O7fOjYd0P69+isVjm1JgfHzVtHyuvl6SfqS70z34BFGL31bDdd24hzKEalufzna0BBG3OvcMpWIBRcchASuCC8hwixhJUeDkcnEPYwS2oTMr+d3oJNyOBBE3hlM5JFWDY+XglstxD2UIVHRepZquXZ+BbeveOUd93AiiiqSoKJdKKDpO3EMZgsVwyUOUVFMl69szBC1jOvx7I/iADLeIYTXFwuv9wubmrGq4sRfNiQpfwYzlVA5ZVQHXZc4xQTLPVXzDrd5eboHabIenXhFELf58YjOWPeM7Wlh1wkaF3GCqJLWMIXiCDLeIYbWo2dZ1ZpWo/HF1skCJ46fAMBw58o1K1gRKvKJzMtyA6sakXudRsBFk1KlDEHEQRK4Zc8JaJkXIgZq1qE7DjSJuBE+Q4RYxnhw3W5M94KdKsjnZZyjibf0IYgAAIABJREFUFiiRsmyA+F5o1urcbNNk2uCNEv/4qdd5ZAWpkp3twSeIWoLziLG1vBpxY3Mtj4ogIlpneYXvbJQYriEnCB8y3CJGUlTkGUslc8tlT8CB0cleJnESb2ERBEgZJe6hjEk1DY8dw811XYq41dCosq1tDEIQREohIogaZEZ7svprZKdH3MREotKept4aNz+jhdYJgn3IcIuYtKIG9Uqs4Fie5Der6VApSYaYSMLqYMPNMU1IigJBZPeUDSJuDB3fRcdBuVRiuv9dlDTaS9IyDEiaxvRxRxBRU02VZMdJBXi16mIiiZQkxz2U2JE1rYEaNz+jhdYJgn1oNY4YWVXhmAZTMsKBchyjETdBECqTcCcbbgbzaRxBxI2hlNag6JxqFwDAi9gKQt3p2rY+2PFpVwQxnKCGiiEnFVApechmqWclvP1MvXsGirgRPEGGW8RIigq3XEbBseMeSkCQXsHwBi2T7epow40HZUQWa9wcql0YgiCKXkuSOn8jltVmCSIuJMVLWWexxo3ldTxKGjHcbNNAIpVCMp0OeVQEMXnIcIsYFtWoLA4MN1nTgshgJ8JDL7KUnIEgikylStrkSR2BpNTfKN3W2RUtIoi4SCRTSEoSU3Md4DlhWV7Ho0RStbozC5ycSWsEwQ1kuEWMxGBRs11p2slqjRvQmPesHbENg/k6LUEQvMWSqVRJ7zyjVMkqklp/na1lDNJGkCBGQVZUpuY6wHPCsryOR0mmgfIKh4P1lSB8yHCLmEZV3aLA8nuEMbxBk7VsZ4uT5EwujA9ZVZlySlRTJWlR9pEVtaE+brQRJIiRsNiT1dbJ0eLjO3vr0ROwcyb1cCO4gQy3iGlU1S0K7Epja5ZTBbxJmK1FMkpskw+PoKRoTLUDCAw3WpQDpDqN62KhgIJjQ9aohxtBDEdqwAESFSy39YkaWdXglsvIW9aEf+uYBrU8IbiBDLeI8UUSWBJwsA0DkqpCTCTiHsqYZLQsinkHhbwT91Aip1QsoOg4TBvWPrKmwWHIwA5knhV2+99FjVfjNvGG008zoogbQYykXgdIVBQcG8VCngy3Cv73UE+6pGOa1OuT4AYy3CImUKNiqAm3xUF6RSOTcLvhcNRjRlI1piSyHdNAOqNAFNl1SkSNt+Gc2Lj2a18p4kYQI2Et4uZnpJCjxaORPYNtGmS4EdxAhlvEMClOYhrMK8dVJ2F2ojlREQhscLCwePVT7PxGPKhxRo2kqMhbFsql0rh/Z1HEjSDGhDUnlRU4Wuh8Barr5USp+67rwjFJVZLgBzLcIiaZTiOZSjNVB8RDQbO/eezIiFslOsKDR1DSNKYazPPQ/y5qZL/O1ho/6u+332B9biCIOJBVla25zo+40fkKoKokPJGzN29ZcN0yOfgIbiDDLQZYy43noaA5iLh1YC83v2aMC8NNUVEqFlFkpBaRPKkjkYJG6ePPQZZBHnyCGAtJUeGWyyg4dtxDAVAjMkbnK4D6UyV9xyitEwQvkOEWA5KislXjxkGvJt971oktAfx0HJkDj2C96SlR4dUusP+9RUnVcBv/N7J0SpUkiLEIFKIZqXPzz1eZzlcAVSXhiQw3O3CM0jpB8AEZbjEgMVQHVC6X4Jgm85uzTEUgoSNTJTnqReYb2KxsZqjofCS+7PVExrVt6Eim0khJchTDIgiuYE0h2l8bWXfCRkUqLSGZliac55wcPzXkBAGQ4RYLLKVK2hw03waApCQhkUx2pOEWSNpz0ItMqtMoiAovVZJ9gzdK6u0laRs6ee8JYgz884gVgRLL0JFMS0ilpbiHwgyypk0ccePIMUoQABluscCSjHDQq4lxw00QhEoT7s4z3BzTQCKZRDKVjnsoEyLXWT8VBaViEQXboojbMOpN8bJ0nfl5gSDiwo9cszDXAeRoGY169gz+7ydz4BglCIAMt1hgK+Lm58Wz36tJ1rJBHn8n4TcHFQQh7qFMSNUoiD/i5p9jfkoT4VFvipfNQe0rQcRFvZHrqLANHRlyUg1BVrWJUyVNfsS/CAIgwy0WPHESNib7oKCZA2+TrGVhm51nuPFUpyUxJE7iL8g8HNtRkpZlCII44Rxk6eTBJ4ixqFfkJyq8iBv7Dtgo8VIlJ3BQmSYgCJAySkSjIojJQYZbDEiKilKhgGI+H/dQalIl2Z/wM9lsRzbgdnL81GlJDKUPORw1Lo8SQRQhKUpQOzkWtqFzMS8QRBywNNcBFUcLOamGUF+qpAFJUSCItB0m+ICO1BgIPHUMRN14UqKStSxsfTDuYUSOw1HELZFMIiVnmIi4UdH52EyUru26LtXMEMQ4JJJJpCSZGXEScrSMxDPcJk6VpHR6gifIcIuBQI2Khc2toUMQPA8869QzCbcjtmlwFTWSVY0JL7RNqZJjIinauCleectCuVQicRKCGAdJZUNojBwtoyOrGop5B4W8M+bf8La+EgQZbjHgG0l5BppwW7oOSdO4SBOQtSyKhfy4k3A74pgmV1EjSVWZcEr4GyqevruomCjiZhteZJtqZghibLx69fjnOt/RwkPmTJT434czjsPXyZnUfJvgCvZ3620IS407vfQKPiZ7f5x2BylLuq7reQQ5ihrJqsbEZiZIleTou4uKiaKivmhRhjz4BDEmkjp+5DoqeGnrEzX+ujmeI9E2KOJG8AUZbjEgM9S40zL4KWgOJuEO6uVWcGy45TJXUSNJVcf1cEaFkzO56X8XNRNFRf1aUlmljSBBjIWsqhOK/EQBT7XqUeLPX+PtGSjiRvAGGW4xwJIalW3oyHCSDiVXCq87qZebX9PH08Li9c6J/9h2DIOb/ndRIynj1+ZYQX9H2ggSxFiw0tqHztfRqTp7x3FScST+RRAAGW6xwFLjTtvQuUkTqKY9dI7h5h8jvPxGQCV9iIVUyZzJ1fcWJZKqouDYKBWLoz5fTZXkw6lDEHHAijiJHyGnVMmh+BHIsSJupWIBRceBzFFGC0Ek4x5AJ5JMSxATCSYMN6/JLh+bs4km4XbETznkSa5YUtSgWF5MJGIbh9dGgRbk0QjqbHMmlK7uEc8H4iRk+BLEmHjqrCZc1401su9HlChVcigT7RkCAStOykW4x3WBcgko5b1LuVi9XSoMvZ1IAWkNSClAWvFuJ1Jx/wdMQIbbeJw7ABinvAOp6FQPqmIeKDlDbxf9A2602453IFbeQyjlcfOCXVD27QTuvsv7m3Kh8qECIAjDrsd6vN7rmtcLIiB1AUofylI3XpLdiRlWF7BFBTK9QKbPu1b6ALkHSLBziPhCCR2VKulH3DhaWPyxOjkz1oiNbRhQuvhwSkSNXBP1H91w84zeOA1vgmAdSVUBt4TCiReQzh0Hzh8EsjOBhVcDqUxk47B8RwsZbkNIZzIQRHHMet6gZUynR9yKecAZBOwL3iW4PTjstl7d+w43tIbcLoz9PNzmxymmqkZcrUGXUoC06l3quT3kvua9D0ewsytnkcf/Adj23cZek5CApAQk0t4lmfYeq72dlOEICspCF7SZl3nPif5P4VaOa9fzTjR9jdEfd0veCXjiOQi5s3hJ/wDEE4eBH983+v8jdQOZHs+QG27Y1d6vfUzuBsTWb/iSaQmJVCq6iJvrAkUbcAwgb3jeIbnH+x8jMmidyTSRLhUB8xSgHwf0k5XrE4BxonJ90psIlT7vdwyue4fdr1zXObn5Y7VNI1bDzckZ6J05K7bPDyjmgYIJ5E0gn6vcznn3R7tdyHnHm39bTABJuXpJyUAy480zqcr1kPu1fzf8dd4lSNceI83L0gepmS9B+NgXPEfuwH7vunJZeex5rLv4JMSvvnTo3yczwKJrgKWv9y5d4c5Dtq4jnckgkWzxulQuA7kznrM3Jbf2vSNAEIRK/9c2jriVS55BFRhcg6PcvjDs8WFGWdGe+HOkLkDK1uxvU97+wb+dUqq3/f1vIllzOzXytpga/fFEyjPy8pW1sJAbebt2Tc2d8ZwmtY+X8vV9f7PWArc8PrnfIGLIcBuPl98KrHi7dxANMcakodf+bTFZiXJNzG/+6nYoYhfe8rZPh/xPjM3AkUP4+ic+jBs/ciuWrrgEsAYA6xyQO+ddB/cHqvfPHfDu2xcwtudE8Iw3f7JPZbyT2r9OjvJYSq65X/NcsnpfSGXQk5WQ1895RtXw77pUrGx4De/E9Q0u/37eqDxmVh8ffj94XeUxtzT6vyh1DzVwlP4aI6e3xujpb9jwqcUZTdK+VPAiwb4BFlyOe8aYb6iZp0f+RoIIqFOB7AxAm+4Zo8Yp4NQu7/fNj1OblpRr/s8xjDulD92F4+hJWcifPQpMmwFE2SPQT8UoF1DKnYcmC95343v8gtSMwti3SwUvAj7kNcNfnwcKVuU4MUdfWHxjrDx6HdnoCDXeQMW7dsveZxUdoGgBBdvzek6CRYk0bl1aRvIHrwdkrWrwVT571bn9uKQHwIO3V87FmvEMvx3czwAp1btOq6E4bwiOcXTg/GHg/CHgQuXaPANImrdeyD2ek1Du8e77tzM9nlc8zFTEcgkYPDqKcVa5bZ0b+vdKP9C7AE7PMmw+ksalGz6I7EXrgZ55wNm9wO5HKpeHvb+fuQpYep1nxM1c0/I50Tb0QLxrUpTLwKkdwIEngYNPeNfWgPdcSq2sdbVrW3/N+tc77H5za16rkVVtTHGSoGVMlKUIrjtsP6JX9yrN3C9aE39mUq7uyeQu73b33Mp51+XtZ4LbXSNvS1n+5vNScRSH6XDnqeEdt5xBhtt4zFwZ2ltLigIn5gbclj4IQEC6dybQtxDAwvpfXC55xttwwy64P1DZuFqVS87z8BinvNv+YwWrfs8IgD+aDuDkw8Cn/65q5AHeBNbIZjalehuGIHSeBZQpQO+C6n3/OalyW0xV/0//f8wNeJuPM7s9gzc/TjQwKY807oYYfJVrqct7b/04pu5/DNfO3A35x39UMcpOeJ83nkHWNdvzImVnAtnplesZgDbD+5vxooVFZ+hvOOLa///PAid3VH9ztxy8xRwAH1wM4Aev9caV6a0aIA1Hj1G5rvO1bjn4bm6ZDeDYo8AX/q7uw6IuhETVwzg87aJrVo0h4x9btbdrjLLR0j1Smfo2qOVyJRXb9gy5YsWwqzXwgvt2zd95F2vgJHb95lFcNH8Fuvt6as5TC8idgVY6g5RYAp5/oHKeNjFXJaSqERc4Y2rTVbSac1Abdj87+nNJOdwNvE+5XPO9Vb4X32gu5IY9bnuOu2D8/thr7jOUch4KruvNA75Bdv5wze2KoTbc+ElI3nyUNyZwBMI752qNubFuZ3pGNwLFhGc4+gbZcOPs/OGacgV4Ttieed56MGuNd927sHI933tPAOe2bcGTj/8t5sx+HbILL/Ne2zsfWPwa4Po7gdO7Kgbcz4Hffg74zWcBdRqw9Fpg6fVeVE6avNHQdFufcgk4sR04+GTFWHsSsM97z/XMA5ZdD8xY6f1G1jlv3s9V5v9zB7z5374w9vsnM6MYe7XrXr/nBPTvS1nvvEm2roWLrGljpkr6jtGGa3kL9tjObetc9TH7Qo3BVXNdb7pgsE+pmUu6Ztfc16rfmW9sBQZad/V2C79PbkgkgUR3cK62E22+mrCLpKowz5+b+A9DxPdCNaVEJSaqE3L/RZMbSLk01MAr2iONu8qG6dmffg8JFLHqlddUn3Pd6iSWrmz2ht+v3RSm1PCiQMX8KMbd2VEMnwHg1M7q4zWGTy1zIKBPS0EwT0/OIKuXpOS9Z3ZG/a8pl71UjMrideHgTjz59buw/tWvxLTpPd7jRRtN12sKYs1jmPhvE2kUyy6e+P53sHD9FZi/cl1NakcSQ9M8alI1xOQ4t2teE2UEcSxEERArjosmSmmKZ07j8e/vQ3LhB7HyNa8f8fx9t30Qs5Zegjfc9ufeA65bc46a1WhjcI766Su56nkZPO97OSu37QvA4LGhUe/aTfN4CIlh5/hoRl/lfiozNEo5msE1llFWT+pQIyTlmnFnh228xjD2gv+x5rlUpqkMj0njul4E//xhLyVpNANteLQ+pQI9cz0DYM7l3nXPXKB7nndbnVo9l8plz+llnfcMB+t8JZ1rtNuV+xeOVB+b6PhJKSOdD3KP57CcuQpYflONYbbAm2vrmE/HVYgWBGDaJd7lqtsB8yyw95eeIff8T4HN3/R+ywWv8AykJdd6Rl8T1N3Wp1QETmytGmkHn/bmbsD7/y95ozee+Vd6v1U9lIpVo652vcudrTxWY/Ad31o1bsYjkR7DgVPjSB3rvK+9L2WhqjL0wcFRP8bRL0BJ5JGxjwIHD49tgPm3/fvjRbkS6aoTVu6ucQhro5z7w+4Pv83CWkMwBxluMeGpUcUrmc5MQbOY8CarOjyPhx8/gvMnjmHVq/46goE1QTJdMaqm1/+aYYYP7AvepK/NwKPf+BYOPr8Dt/z9veGNebKIYrXOEYCoLMDOwe9hztTXYtqrr4tlSLkzp7HpK79D/8INwOXXxjIGlpEnaEniqc3WzAuCUIkMKgD6Wz+golNJU9ZHSWU2xnmucv/CkaHpzrWbdDFZk6ItD03Xlru8lGE/pTuZGfk34z5eqRssOROnN9Wmbzt6JWpxsDlPvE/Cr6FO1dRRD3+s5vaQdP9xHivaNUZZ5Xq4MSt3e0ZY70JPjKNnnpd+1TMX6JnvzQf1GpaiWI0QoEHjxXcqDDfsam/bg4A2dWjUrAUpUhPVig5B7QdW/YF3KRWAQ097kbjdjwAPVRwk05ZX6uKuB+asrzs9zTZ0dE2ZNvKJUsEzlg78zjPWDv1XNSukfzFw6QZgwVWeodY9u67PGkEi6X232tT6X1Mueb9PYNxVDL3gnB52vvgX/cTQ5+vI1rkJgJsG8H/vrxp1RQfIDWBVwcSqpQC+OdJ5BTE5NEOmZx4wc/UENf+V7BLqHUqECBluMSGpaqAYGBdBxI2jpp2ylg2ajbYNwwyfWqycxZ3ilaz4/fbic0wEtYHUDmBUUrKntjaa86hULCJv5aIVJ0lWRJ2Uvta8X7nkGRoJiZ80xaD2xawad0PSrPSKMnGtorFfl1mj9FZ0hj1e8AyX4Y8Fasl+/eawqJUyxTPCpleMiZ75lYhZxThjJQWp1qkQsgjIcKpCTA2u5YmUZ+wuvBp4/f8BztTUxT11N/DEP3lGwZJrve9+8WvG/b4tw/Da+hTzwLHNnqF28Eng0DNelBsApiwFVr7dM9IWXNVYVkWrEROeIatO0glUzI9f1+7o2Pv0r3Bu/wu4/LrXV8+npAxkerF/94vYv2sfXv2RvxxphIVdV0kQTcLJitZ+SIqCouOgVCy2XgmqTmx9EGIigZQcnWzxZJE1Dbahx943Jyoc0+RO8SopSRATyVgNN7vZ2oUOQRAESKo26oYzqPvgyKEzAjHhedZ5QhBqMg8aiNi3inLZM96KjhdtYEBYgnV8w83JTXKum7IYmPJR4IqPepGofY950bg9P/eUrcUkMP+KisDJddXyhKID9/DvsVragUvP7gU+8+lqGt/US4DVfwgsuNIz1rRRInK8k0wDyb5xHT6nDqp4+ikd6679e4jDIph7Dt2NF0spvPqyt4Y9UoJoGWS4xcREDXCjwDYMyFqWKwMok+1CqVBA0XGQkvmTJ24U2zTQPS1Gz2gTeBLM8aYCBzLPnEUro0RW1FF/I79PYlO1rwS/iCIgViKfRF0kkkmkJLm+VMl6yfQAl73Vu5RLwJHfAy887BlyP/9r79K/xEvxPboRQtHGlVOBnDsXWPveSurjFYA6pXVj4pigr6g5sq+oYxi0RhDcQYZbTEzUADcKLGMw/vq2BvEnYcvQO8Jwc0yTy6iRpKiNpw+1kCDixlm0MkokVR21xo2Z2leC4ABJ08asFZ00YgKY9zLv8rpPe0qOux/12gxY54D1H4DRfQn+8+5v4VV/+iksv/rV4YyDY/x5bDQBFzvHX0YLQZDhFhMNFTWHhK3rXNW3AUMn4a4pDRRDc4ptGlzWackqKxE3WpTHQlLUUecf24+4xdg8nSB4QR7jPAqF3gXAS2/xLhX0PS/ALn2fHC1j4DvvRuvl5phGbI5zgmgW0hqNiWpufIyGW6uadkZIpsZwa3fKpRIKtsVnxE0dPQ0vKmzTAAQBkkJ1OmNBETeCmDzeeRTjXFdZC+l8HR1ZHXvP4JgmJA7XV6KzIcMtJlgw3Jpu2hkjcgcZbv6xwWPEzRO+iDHiljMgZRQI1AdnTMZqSVKNuNFGkCAmIu60cIsMt3EZb8/gZbTwtQciCNrVxAQTqZKGwV06lK90N1raQ7vBszKirEaYPjQKjkEL8kSM1ZLENnSIiSRXarMEERdSzGnhvkFCjpbRqdbFD/2NXNfltoac6GzIcIuJQFUypgm/kHdQzDvcTVq+98zSB2MeSfgEdVocR9xct8GGwi3CztGCPBGyolZakgzt32UZXu0rT2qzBBEXY9WKRoWl615aOIfrRBT468DwiFvesuC6ZfreCO4gwy0m0rIMQRBjS5Wseun4iril0hKSqXSsaXhR4f+PPMoVy6oGt1xGwbFj+XyHU1GXKAmi/rnckMdtXae0K4KoE1lV4eRycMvlWD7fNnTIijqiRxnhISYSSGeUEU5yvy6RHHwEb5DhFhOCKCKtZEZsmsLEdUs4d/73KJcLQR0LbzVugJcu2RE1bhUvLo8Li28UxJXSahsGl99blPippMM3NDy2CSGIuJAUFa5bRt6Ox0llG3pQQkCMjqyN3DP4axM5+AjeoHYAMTKWOECrcV0XZ8/+Gnv33QnT3I0ZM96MbPk9AMCdqiTgTcJ+k+B2xj82eKzVkmuNghjaNjg5kxbkCQhSiIbNQbauo2fGzDiGRBDcEThAckYsKraWTo6WiZC1kWJZfrYTOfgI3iDDLUbGEgdoJYOD27B372dx7vx/IZOZhxnTN+DEiR/BSqUBcBpx07SOiLjxLE5SreGMKRWY1MImJFC2HfYbWYaOGdqyOIZEENwxRGhsSvSfbxsGlC7+HLBRImvZQH3Th+dSBKKzIcMtRsJs3GlZh7Bv3xdw8tSDSKX6sHTp/8TsWe+EIKRQdvM4dfL76Jo3m7saNwDIaF0YOHYk7mGEjmMaEBMJJCUp7qE0TND0NIZaxFKxgKLjQKYFeVyqNW7VOch1Xdj6ICnUEUSdjOUAiQrbGETfrNmxfDYvyFoW+tkzQx4LShE4dF4TnQ0ZbjEiqSounDzR0vfM5wew/8AXcfTotyEICSyY/xHMn38LksnqRmz5JXfizPGtmP+aYyiJJxCLm3ASdErEzUv307hU96umD0W/mQnUOGlBHpfRWpJ4KpNFSr0iiDoJUo5jExozqMZtAjKj7Bl4LkUgOhsy3GJEUlqXKlkqWTh8+F4cOPhVlEo5zJr1dixa+HFI0vQRf5tIZCCcfgvKXfdgx86P4vL1P0Q63deScUSBX2jsui6XRk292KYJmdM6rTjFSWyORV2iRFZGRkUtw2uzwWMkniDioBpxi36uK5dKcHImZJUMt/Hwe+25roszZ36JjLLAWycEAVIm+rpEgpgMZLjFSCv6v7huCceP348XX/xnOPmTmDLltbjooj+Hpi4Z93XOoIATOy6F9Lqd2P7cR7Fm9dchiulJjSUqZC2LUrGIgmMj3cZNgh2O67T8In3bNHDixE9g2Ucwe9YfIJ0OP7pb9aTyafRGRVKSICYSQ6KivugPefAJoj5GSzmOCt/pQqnN4yNrWZRLJRzY/2948cBnkEx2o5jfAElRIIgkrk7wBRluMSKpKvJWDuVyqeEeLFWlyM/CNPegq2s1Lr3sX9Dbc3ldr7d0HUJ+Fi65+H3Y8fwdeGH3/8LFy/4PFxEsP43LNvQ2N9xMbgunRdHrnWOLv8WO538JADhw4IuYMX0D5s59PzRtaWifzbOoS5QIgjDCeeS3CcmQB58g6iLOGjdL9yLklNo8PrKmoW/pebx44DPo738lDOMFFKZ9D9r0FXEPjSAahgy3GPGV9/KW1dAm88LgVuzd+1mcP/8MMpn5uOyyL2La1OsaMrpsQ0dGy2LGjJtgmHtw8OA90NRlmDv3fQ3/H1GTCQw3A11TpoX2OcWigQsXNuHcuWdw7vwzsO2j6O5eh76+K9HXeyUymXmhGrq2aSA7Nbz/L2ymrhgE+jZ5UeBFd+DI0W/i+PH7cez499HX9wrMm/tB9PVd1fLvMIi4KWS4TYSkqkMjbpVUSYq4EUR9iIkEUnImaOgcJYGjhQy3cSlLz2PuK49Dlddi5Yp7YNvH8ORvb8Ssq7chl9sPRVkY9xAJom7IcIsRP53MMc26DLdc7iD2vfh5nDr1UEUp8n9h9qx3QhRTDX+2bejomzUHAHDRojtgmnuwe8/fQ1EWob//FQ2/X5T4m0rf29gqhhtqur4drluCIKTQ1bUKfb1X4Nz5/8bp049445DnoK/3CvT1XYne3itaXifo1S7wGXE7cvTbmLpmDwrn52DFNXdDFNO4eNnfYdHC23H02Hdw5Mg3sGXrH0FVl2De3A9i+vQ3IZFojXqmTWphdTO8l2SwEaQaN4KoG0lVg3knSmzTT22m83Uszpx5HGfse2CezOCiFZ+AKEpQlIU4v/Uq9Kz6LZ7d/G6sW/sdZDLz4h4qQdQFGW4xUm9ufD5/tkYpMoWFC27DvHkfQjLZ/MbUNvTAABIEEZcu/wI2bXoHnttxG9av+yFUdVHT7x02ck3EbTJMZKjNn/+n6O15Kbq71yKR8FIyXdeFZR3AwMCTGDj3JE6dfhjHjn8fAJDVLkVv3xXo670SPT3rg9c0g+u6sA0+a9yOHv0OXnjhfyB/diYu7FgP8S3V2sl0ug8LF9yK+fM+hJMnH8Shw/+Bnbv+Env3fQ5z5rwbc2b/4aTr4Bzqz1M3w3tJBhE3MnoJom7CbO0zHkFNKkXcRuXcuWew/blbkZEWYtsjAi5eVAyeM0+JkPe9AekVj1eMt+9ClmdJXgqwAAAgAElEQVTFOFqCqA8y3GKk2qR4dAOkVMrh0OF7cfDg11AuW5g18x1YuPBjkKTJpc+5rgtL14dM9smkhpUrv4bfb3wztm2/BevX3Y9UqntSnxMWmZoat0ZoxlAbjiAIUJSFUJSFmDPn3SiXi9CNHRgYeAIDA0/i8OGv49Chf4UgpNHTsw59vVeir+9KZLOXQhDqr2Ms5h2US0Xu6rSOHv0udr3wt+jvfxUObp4Hxzg56t+JooSZM9+KGTPegnPnnsahw/+B/fv/BQcP3uPVwc37wIQCO2NhmwaSqTSSaT7EduJEVlQYNf2NbMNAOpNBItl4FJ8gOpXhKcdR4a+BJE4ykguDW7F12x9Dludi2aK78XT+9iF7LSdnIp1YhjWrv45nN78bz26+GevWfndUJW6CYAky3GIkkEwfNuGXy0UcP+EpRebzpzB1yutw0UV/AVW9qCWfW3BslEvFEXnxmcwcrFjxZWze/B4899zHsGrVv0MU2TtE/P5cExlurTDUJkIUk+juWoXurlVYuOBWlEo5nD+/EQPnnsTAwJPY9+Lnse/FzyOZ7EJv78sDQy6TmT9ubZfNYdTo6LHvYdcLf4P+/muwcsWXcOKpe2Cb+8Z9jSAI6Ou7An19V8A09+Hw4Xtx/MQPcez499HfdzXmzvsg+nqvbKgOzsmZ1MOtTiRNG7LhtPVByBqlXRFEI0iqBuPs2cg/1zZ0CKKINEnaD8EwXsCWLe9HKtWHNWv+EwmhFwBg1ewZ7Ipqc1fXCqxZfS82b/kjPLv5PVi39tuRqB8TRLOwtyvvIPxNeT6XA4BKj5HHsHff55DL7UV31xqsuOxu9PSsb+nn2uOkV/T2XI6Ll/1v7Nz1V9iz9/9i2dL/r6Wf3QpSaQnJtDRkEgYmMtRWYv68P0Fv78vQ3b0GiUQ4C10ioaC//2r0918NAMjnz2Dg3NM4N/AUBgaewOnTPwcAyPJs9PVeWUmtfPmIhcLhrE7r2LEfYNeuv0Z//yux4rIvQxQlyKo2pEfYRKjqRbj44r/HokV34OjRb+PI0W9iy5b3QVWXVurgbqyrDs4xDK4M3jgZrippGTp57wmiQWRFxdnDByP/XNvwMmd4UIOOilxuPzZveS8Sooy1a74BWZoBAEim0oGzt1QsoOg4kCvrRHf3Wqxa+W/YsvX92Lz5vVi79ltIpXpj+x8IYjzIcIuRoMbNNHDhwhbs3fsZnL/weyjKQqxY8WVMnXJtKBNyICE8xgZt1qx3wDD34PDh/4CmLsHs2e9q+Rgmi5zNwtZ1GMYLOHHiJ7EZahORTk/BjOk3Ysb0G2vq456q1Mc9EtTHadolgVplT8/lwWaaBwPk2LH7sHPXX6G/72qsuOyewLiSVQ1Fx0GpWGgo9S6d7sPChR/F/Pl/XFMH9yns3Xcn5sx5T6UOrn/M19umwV2KaVzIqoZiIY9iPo9kOg17WAo1QRAT4zV4ji5V0nXLAIQRJQ+djm0fw+bN74XrlrF27beQycwNnpM1LaiLD9bXGsdob+9LsGrl17B124ewecv7sGb1N5FKUfYBwR5kuMWIlFEgJssYxHewcdPvkU5PwbJlf4dZM9/elFJkvfiT13gSwov/f/bOOz6So8z73+6enu7JI42k0SittKvN6w0ORzA+MMlgzIGxScYcOZngs8Fg4sHBEQ4wHNwBNjbxbJLBxoTDhANefIcT2N4clcOM4mhy6u73j56oLK2k1S7z+3xGVV1d3V0zqq6q3/M89Tyb3kcifpJjxz+K3b6RmponrVp7lgOb047u/hMPP/JVQFg3RG0+VO6PexWGoRGJHmRy4n/z++O+Q1/f7YiiFbf8IhCNdU9Ahobv5sjRm6mtfRrnnfe1Co1YSTARx+7xLvnelfvg/i+/D+6L9PZ+hcbGK814cLPsg0snlve8v0UUY1Al4lisVpKxCO6G6h6PKqpYCgpOfgxdX7WAztnsJOPjf2J84o+Mj/8JQRAxHO3YnC2r8ryzDenMGH997NXktCjn77sTh6Oz4rzqdBU1bsVYn9MEo7W1F3Perq+w/8DbePyJ17Fv77dPywlcFVWsBqrE7QwiFj/M1qt70JQ0ba1voKPjXWsySJQ8x81N3ETRwq5dX+KRR6/iwMG3c9GF91RIr84kYrHj+C9+GItrkoaGf2Drlo+clWYNgiAV98e1t1+HpiUJhx9haPhHjIz8iC0vVtEtI8DqBas+HQwP/5gjR26mtuZidk8jbVAKgJ1aJnErwNwHZ+4NjMdP0tf/TYLBexga+gE+39NpbX19xT64VDxWDHVRxfwo92zr8NaQilZNJauoYqlQ7A4wDDKp5IpZSRiGTjR6kLHxPzI+/kcikScAHVmuobb2ElKpQTKdj6A2nWJy8kFqap68Is89G5HNhnn8sX8knQ6xb9+3cbl2zqijOl3F8AmzadwKqKu7lPN2fYkDB9/BE0+8kb17v7EuBcFV/O1idURDVcwLw9Do6fkaj/7laiTZIDfwYjZv/sCaSXaKGrcFYr9YLC727L4Vw9B5Yv+byOWW5sVxpWEYGr29t/LwIy9CUpOMPrqHXTu/cFaSttkgSTZ8vr/nvF1fxpF9LVZnlqPdb6S391YMQzvTzavA8PA9HD7yPmprnsru3bciSeqMOoVQBnN5TV0OHI5Otm/7Vy5+6gNs7LiBaPQQjz/+Gh5++AUMDd2NrqdJx+NFQlLF/CjXiuq6RioRrzonqaKKJaL8PTodZDITBIP3cejQu/nTA0/ikUevpLv73wGdjvZ3cOEFP+aSpz3Erp1f4ILzf0Dwwe2Icpa/PvYq9h+4jkRi7ffZnWnkcjEef+L1xBPd7Nl9K17PBbPWKzeVLDn/mn3NVV//XHbuuIXw1F94Yv+b0bTU6jS+iiqWgarGbY2RSg1x6PC7CYcfpqHhch77dQqPb2UDNy/YhujiYzXZ7R2ct+vLPP7E6zh06EZ27/7aktzarxQSiW4OH76Jqchj1NdfRvDhDUyePLDm7VgrGLFOjv5sI8+4oZ2Tp/6N0dHfsGPHZ7HbO8500xgO3svhIzdRU/OUOUkblIjbUhyULBbl++CCoZ/R32fugzvV9XkcbRKKY/kx9P6WUB6SJB2Pg2FUNW5/ozAMDU1LomlJJMmOxVIVfiwWqr001rnrFx+uxzA0IpEDjI//kfGJPxKJ7AcMZLkWX+0l+HxPp7b2abPu6RUEgfGjKk0tb6Hj7w16er/Kg2O/p631tbS3X4fFcu6/x5qW4on9byYaPch5u/6T2tqL56yrlDnLKggT59uK4Pdfga5nOXzkJg4cvI7d530VUVzYOVYVVaw2qsRtDREM3sex4x/BMHR2bP83GhtfwiHr+9Y8/ksqHkVWFx+rqbb2YjZv/jDHj3+UU6c+T2fne1e5hSUYhs7AwHc4eeqziKLCzh1fwO9/IeED3yYV+zOGYZyTHrXS8RiC7mT37q8SCt3HseMf5aGHr6Bz0020tPwjgnBmlOXB4E85fPgmamqezJ7dt80bRkEtc76zWhBFhabA1QQar2Jy8v84deoLtF7yGFn9a4yMNFJff9k52T9WCmpZSJJCMN/59r5WceZgGAaalkDTk+haokiySmXlxyk0LZEvM88XzulaCk0vvz6JrifQ9UzxWaJoo7X1tWxoe9O6jee5nlBucrwQMplxxif+xPj4H5mYeIBsdgJzn/ZeOjqup873dFyuXQuO8blslmw6hc1ZS3v7ywkErubUqc/R23cbQ8M/ZtPGG2lqeukZEbSuBXQ9w4GD7yAcfpidOz5Pff1z5q1fucctbyq5gGVGIHAlup7m6LEPcvDg9eza9eVV9T9QRRWLQZW4rQFyuSjHjv0zwdBP8bj3sWPH57HbNwCmbXxsYmJN22N6olqaWWZL87XE48fp7bsVh2MzgcCVq9S6EpLJAQ4feS/h8EP4fM9g+7ZPFoNj2pwudC1HNpU8J2PYpOJmLDJBEGhsfBE1NU/myNEPcPzExxkZ/TU7tn9mzfccBoP3cejwe6jx/h17dn99wdh3Stket9VGYR+clOvkh597GZufp3Hg4Ntxu/fQuel96865zmIQiexncPB75HJRRNGKIFoRRSuiqJipMO04ny/WE2aeK+XNY6vNlCCn43FSi9j7ut5hGBrj4/+PgcHvMjHxZ+p8T6e5+VXU1l58xoQdp4tUOsjQ4A8YGv4h6XRwCVcKSJINUbQhSXYkSTVT0YZi9SMWjiUbkmhHlGxmXrITDj9Mb+/XGBz8Lza0vZmWltectRq4VGqI4eGfYGAgy16scg2yXIMse4upKNpOS8BTdPIzy1hnatX2m1q18T8SiR6gqFXz/T2+2qfj812yZJP/6cG3FaWBHTtMz7vHT3yCo8c+yMDgd9m8+UPU1jxl2d9tPcIwNA4dfjfj479n29ZP0Nj4ogWvsTld5NJpcpnMojRuBTQ3vwJdT3P8xL9w6PCN7NzxhXUZ37aKvx1Ue98qIxx+lEOHbySdDtLRcT3tG66reOkVh5Pxwf41bVMqFsW2xH0sgiCwZfNHiMdPceToB7Db2/F49q1K+wzDYGjo+5w4+SlAYPu2TxMIXF0xsRYWl6lY7Jwkbul4rMLjlaL42bP7doaH7+b4iU/w0MOX09n5fpqbXrkmGqVg6GccOvxuvN6L2LNnYdIGpUlxNTVu05FOxIn0umhy3IyzNUhX9xf462PX4PM9g02bbsLl3LZmbVkODENnfPwP9PbdTjj8EJLkRFUD6Foa3cig64VPGsPIrsgz97wJxoQbiAy3ULczgcVurMh91xLZbJih4R8xMHAnqVQ/VmsDjf4XMjb+e0bHfoPN1kZz8zUEGq/Cal1b0/TlwDB0Jib+l8HBOxkb/x8MQ8dXewmtLa8pki1RsiOJZeRLsudJWiGvLHtsaGm+hg0b3kpX1y2c6vo8ff3foqP9OpqbX3nWmIvFYsfo7buNUOjnGEZu3rqiaEWWa00yZ/GWETtvqbyirAaLxV0UBhT38+Y1bpnMWNEDpKlVmwREPO49bOy4Ht8itWrzobTloVLQ4nafxwXnf5+R0f/m5MlP89hj11Jf9xw6O2/Gbm9f9vPWCwxD58jRDzIy8ktzDlxkuKKCsDoVj5GKx5BkGYvVuqhrW1tfg25kOHny04iilR3bP3vWCoKqOPtRJW6rBF3P0t39JXp6v4ZNbeGC838wK9FR7PY1jf8CZpDd5QR2FkWZ3ef9J4888hL2H3grF114D6ratKJtS6WGOXL0/UxM/ImamqeyfdunsdmaZ9QrxKBLRiNL2lNwtsB0sFH5PxIEgaaml1JbezFHjtzMsWMfZnTkfrZv/9SK/x/KEQr9nEOHbsTrvZC9e25ftIcti9WKJMurssdtLpQkqW6amp6G338FAwPfoaf3qzz88BU0Nr6YjR03zNqnziQ0LU0weA99/d8gkTiFogTY3PkBmppeNudeFcPQ0fUsum6SOiNP6PTZUiNTcVyoq+kZHvzJnQS2bEJ3DNLytBAnhl5NOPNsAoGrqK29ZF1LlyPRgwwM/Beh0H3oehqv5yI6N91Eff1zEUUZXU8zMnI/A4N3cvLkp+nquoWG+stpbrkGj/v8dWdGm8lMMDx8N4ND3yOZ7EOWa2lrfSPNza/AZmtb07a4nNvYs/s2pqYe49Spz3H8xMfp7budjR3vorHxJeuyXxiGQTj8CL19tzI+/gckyU5Ly6tpa309Vmsd2ewU2ewk2WyYbC6fZsNksxNl+Uli8eNks5PkclPzOIYSi0ROEl10XNbPRObrPPzIl4lGzf3XVmsddb5Li3vVZHnlwpQUHG3MpiEXBAF/w+XU+Z5Ff/83zP1vDz2P1tbX0tH+9rN2/5thGBw/8QmGh39ER/s72dD2xkVfWxL2Rkkn4ksOtbOh7U3oWpqu7i8gCla2bfvXKnmr4oxg/Y285wASiW4OHbqRSHQ/gcDVbNn84Tk9Rip2M3DnWu7VSsViuDbUL+taWa5h957bePTRq9m//61ccMH3V8RVrmEYBIP3cPzEv6DrObZu+RjNzdfMOTDaHCWN27mIVCKOy1c36zlVbWLv3m8zOHgXJ099mgcfej5btnyYQONVK96HQqFfcOjwjXg9F7Bn9+JJW7GtDueaatyK8XnygglJUtmw4c00Nb2c3t6v0T/wLUKhX9Da8mra2992xj2SZjITDA7eSf/Ad8lmx3G5drJzxxdoaHj+gnspBEFEkpQZYRiWivuPPUS9+8nUBJp56Bf/yaXvfCpj4//NyOh/Y7U2EGh8MYHAVTPiIp0pmGTsVwwMfJepyGOIoo1A40tobrl2hkZVFBUaG/+BxsZ/IBY7xsDgXQSD9xIM3YvTuZ3m5mto9P/DGY3VZBgGU1N/YXDwLkIj/41hZPB6LmJjxw00NFx2xjVcHs8+zj//TiYm/pdTXZ/nyNH309t3Gxs7/omGhsvXxeLVMHRGx35Db+9tRCKPI8u1bOy4gZaWayvIkqLUoyiLn/sMQyeXi+XJ3mQZ6QuX8tlJsplJrM4sWY5jEzvZuPFGU6vm3LFqv89iwvpIkkJ7+9sIBK7iVNct9PXdzvDwj9m48Qaam15+1u1/6+r+IgMD36a19XV0dFy/pGtVRxlxi8WWFbaho+Md6Hqant6vIEoKWzb/87oT/lRx7qNK3FYQhmEwNPxDjh//OKJoZdeu/8Df8Px5r1EcDgxDX9O9WqloBNsyNG4FOB2b2bXzizyx/00cOnwT5+368mlNTunMGEePfpCxsd/i8VzIju2fWdCko2T2cGZDFKwW0vEY9W3tc54XBIGWllfh813C4SPv48iR9zE6cj/btv0rirIyGsjQyC85dPgG3O597Nlzx7L2uCh2x5pqlIvxeaZNyrLsobPzfbS0vJqu7i/R1/9NBod+QPuGt9La+tpFmX6uJBKJbvr6v8nw8I/R9RQ+3zNoa3sjNd4nr/lCoPA/SsVipMN2tm//GIbxIcbGf8/w8I/p67+D3r7bcLv3Eghchb/hCmR57UMGpFJDDA5+j8GhH5DNjmOztbN584cINF61qPY4nVvZtvVjdG56L6HQfQwM3sWxYx/m5MnP0Nj4IlqaX4XTuXUNvomJXC5KMPhTBgfvIhY/hiQ5aW5+Oc1N1+B0rr/YjbW1F1NT81TGxn7Lqa5bOHjoepy9X2PTxnfj8z3jjCxgdT3NcPBe+vq+TiLRjU1tY+uWfyEQuGpOb7dLgSCIyLI73782zFv3f7/0UnZd+lwufM6bTvu5i0HRmdAivMAqSgM7tn+alpZrOXH8Exw79mEGB/7L3P9W+9TVbuqKoLf3Nnp6/oOmwMvY3PnBJfe30pohTioRnzWG22KwceON6Hqavv47EEWFzk03V8lbFWuKKnFbIWQyExw9+gFGx35DTc1T2LH9s6hqYMHrCgvMVDy+JsTN0HVSsdhpx2qqq7uUzs6bOXnyU3R3f5mNG5cm/SogNPJLjh37CJoWZ3PnB2htfe2ipIBqPgZdYfI617DYWGQ2Wxvn77uT/oFvc+rUZ3nwoeexdctH8ftfeFqTycjIrzh06J9wu/eyd5mkDcwAp2tpKjld4zYdqtrEju2fpq319Zzq+jynuj5H/8B32NhxPYHA1atu/hWe+gt9fbczOvobBEEm0PhiWttej9OxeVWfOx8Uh4N0wnROojpdCIKAIFhpqL+MhvrLSGfGCAbvZXj4bo4d+zAnTnyC+vrnEghcTW3NU1ZVam8YBpOTf2Zg8LuMjv4WMKirexYtzdcu2+GIxeKgufmVNDW9gkjkcQYG72R4+EcMDt6Jx3MBLc2vor7+eaetyZwL0ehhBgbvJBS6D01L4HLtZNu2T+JvuGLdOwARBIH6+udQV/dMQqGf09X1RZ7Y/0Y8nvPZtPE9a+YEKJeLMjB4F/393ySTGcXl2smunV+ioeF5Z0yLVLCeWSsUnZMsYS53u3Zx/vnfY3T0fk6c/BSPPf5q6uqezebOm9dFqJm5MDB4FydPfYaGhhewbdsnljW3FYlbLEo6HsPuXp63VEEQ6Ox8P7qeoa/vdkRRZdPGG5Z1ryqqWA6qxG0FMD7+Jw4feS/ZbJjOzvfT1vr6RS8oCsQtk4gDyzNfXArSyQSGoa9IrKa21jcQjx2nu+dLOByd+P0vWPS12ewkR4/9MyMjv8Dt2s2OHZ9dkilWwT69MHmdS9B1bUk2+IIg0tb6Ony1T+fwkfdy6PANjIzez7atH8Nqnd3ccj6MjNzPwUPX43bvYe+eb5yWGZnqcJKYCi/7+qUinYgjCCJWdX4NmtO5hT27byUcfpSTpz7D0WMfpK//DjZteg/1dc9dUQmqYWiMjv6G3r7biUQew2Lx0r7hbbS0/OOSzLZWCwWNWzIanTUUgGKtY0PbG2lrfQPR6AGGhn9MKHQfodDPUJQAgcYrCQSuWlHHB7lclOHgvQwM/BeJxElkuYYNbW+iufkabLaWFXmGIAh4PPvwePaxZfMHGRr+MYODd3Ho8I3I8icIBK6iuemVRQ/ApwNNSzEy8gsGBr9HJPIYoqjg97+QluZX4XKdd9ZJ7AVBorHxRTQ0XM7Q8I/o6flP/vrYNdTWPI1Nm96N2717VZ6bSgfp7/8Wg4PfQ9Ni1NZewoa2z1NT89Qz/huaApA1FFLFokgWCxZlaQIGQRBoaHgePt+l9Pd/k57er/DgQ8+nteUfaW9/xxnRps+H4eC9HDv2Eep8z2Tnjs8vm5hX7HGLx6kJLH+fsyAIbNnyEdNssuc/EEUrHe1vX/b9qqhiKagSt9OApqU51fVZ+vu/icOxmb17voHLtX1J91DK4iitBVJ5DdVKuPwWBIFt2z5OItnN4SPvxWZrw+0+b8HrRkd/y9FjHySbnWLTxnfT1vbmJWs6LFYrFkU5J4lbJpEESsGRFwuHYyMXnP99+vpup6v733kw/DDbtn6chobnLfoeI6P3c/DQu3C7zjtt0gYmKZgYGjiteywFqVgMxW5HEBcnOPF6L+SC83/I2NhvOXnqcxw4cB1u9z46N72Xmpq/O622aFqCoeG76e/7JslUHza1jS1bPkpT4KoV2Re6UlAcTiJjo8gxZd5xQRAE3O7duN272dz5AcbGfsvw8N309H6Nnt6v4PFcSFPgahoanr/sfhOLn2Bg4L8IBu9B0+KmUGf7v9HQcMWqacCAPDF8I22tr89r+O6kv/8b9PV9ndraS2hpfhU+36VLHqcSiW4GBu9iePjH5HJT2O2b8uadLzkn4qOJokxL8zUEGl/C4OCd9PR+lUcevZL6+ueyseOGFTP5jMdP0tt3O8HgvRiGht//Aja0vQmXa+eK3H8lsNZm4alYFNXlXjZhNfe/vZVA4Cq6um6hr/8bDAfvYePGG2gKvGxdOJ8ZHf01R468lxrvk047hprVZs4LqZjpVXK686+lQhBEtm37BLqRoavrFkRRWZKzlCqqWC7O/Jt5liIWO8ahQzcQix+jpeXVdG66eVk29eo88V9WAwWis1KxmkRR4bzzvsqjj1xZ9DQ51x6rbDbCiRMfZzj4E5zO7ezd860lE91y2Jzuc5K4Fcz9FmMqOR2iaKG9/a3U1V3K4SM3ceDg2/H7/4GtW/55QY9mo6O/5uDBd+Fyncfevd9cEc9jqtNJeg0dyKSXsXehYP7l811KMPgTurr/nb8+9krqfM9k06b3LHnfUzo9ysDAdxgYvJNcbsokgp03U1//7HXpDEC1O0jHY1hkGVfd4jSAkqTg978Av/8FpNJBgsP3Mhy8myNHb+bY8Y/R0PA8mgJX4/X+3YLWB7qeY2zsdwwMfIfJ8IOIopWGhhfQ0vJqPO49K/EVFw1BEKmtvZja2ovN+GlDP2Ro6AfsP/BWFKWR5qZX0NT0smI8ydmg61lGx37L4OBdTE7+H4Jgob7+ubQ0vwqv90lnXDO0GpAklba2N9DU9DL6+r9VNAdubHwRGzuuX7ZHzPDUX+jtvY2xsd8iiirNza+grfUNax7DcjFQHA6i42Nr9rxkNLpkz4izQVHq2b79U7S0XMvxE+b+t4GB77Jl84eorb14BVq6PIxPPMCBg9fjcp3H7t23nvaeRUEQUB1OUrEI6fjSvUrOfk+J7ds+g65nOHnyU4iiQmvLq0/7vlVUMR+qxG2JMAw9v5/o37BY3OzZcwd1vmcs+36FxXl6jTRuyRUmbmCaUu3efRuP/uWl7D/wVs7fd9eMQXZ8/E8cOXozmcwo7e1vp6P9HYji4mKozAXV6Sx+n3MJSwkOOheczq1ceMGPTW1Iz38wOfkg27d9krq6S2etPzr6Gw4cfCcu1y72rRBpg/y+j0QCQ9cXrQU7HaTjy/MWBibpbWp6GX7/C+kf+A69vV/loYdfQKDxSjZuvGHBkAux+An6+u4gGPwphpGlvv45tLW9Ea/ngmW1Z61Q2OMmWiw0tG9a8vWq0kh7+1vZsOEtRCKPMTR8N6HQLwgG70FVWwkEXkKg8SUzTBzTmTGGhn7A4OBdpNNBVKWJTRtvoqnppVitvpX6esuGqjSyseNdtG+4jrHx3zE4+D26ur9Id89/UFf3bFqar6kw0Uulhhgc+gFDQz8kkxnJf593Ewi8dF2YxK4FLBYXGzveSWvLtfT03srAwHcIhX5OU9PL6Wh/+7yEtwDD0Bkb/z29vbcxNfUoFouXjvZ30tLy6nXRL+aCancw1te7Zs9LxaPYXCtn1uhy7eT8fXcxOvrr/P63f6Su7ll0bnovdvumNRU4hMOPsn//W3E4Nq6I5UcBqtNFZHQEw9CXJRidDaJoYeeOW9D1DMePfxRRtNLc9PIVufd6gWFoZLKTaLkoNtuGdeFJ9nRgGAbR6AGGg/ciChY2b/7AmW7SklAlbktAOh3i8OH3MjH5AHV1z2L7tk8uaw9ROaYH7lxtFDc0r8Aet3K4XNvZufPzHDhwHUePfoAdOz6PIAjkcjFOnvw0g0Pfw27v5MILvrpi+x9Up+ucDAdwOhq3cvs3m/YAACAASURBVIiizMaOd1Jf90wOH76JJ/a/MR+e4kMVxGx07Hd50raTfXu/taIxftS819RMKrlsQrUUpGKx05akSpKN9g1vobnp5fT0ftVcfI78nJbmmSEEDMNgMvwgfX23Mz7+B0RRpanpZbS1vnZdb/Yvh2J3oGWzJMKTxfiIy4G5Z+x8PJ7z2bL5w4yO/pqh4bvp7v4S3d3/Tk3NUwg0XoVqa2Fo8HuERn6JYWSprXkaW7d8lLq6Z65LjaQoWoqOWhKJHgaHvsfQ0N2Mjv4Ku72DxsYriUT2Mzb2P4CBz/cMWpr/FZ/v6evy+6wFZLmGzZ0309b6Orp7vsLQ0PcZHr6blpZXs6HtLbMGQdf1DKHQz+jt+zrx+AlUpYktmz9MU9PL1pVp8VxQnM613eMWjeJtXNgB2lJg7n+7DJ/vGfQPfIuenq/w4EOXIUkOVLUZm9qCamupTNXWFd0XF4ke5PEn3oCqNrJ377dX1KRYdToJj4TM/Apo3AoQRZnzdn2J/QfextGjH0QUrAQCV67Y/VcahmGgaQkymTGy2XEymfwnO04mM0YmM062eDyeDyBvAKAojfgbXoDff8VZtz83lRoiGPwpw8F7SSROIghWGv1XnOlmLRlV4rZIjI7+miNHP4CmJdm69eM0N71yRTqsYjcnpLUylUyu4B636Wiov4yNG2+kq+sWHI4teDz7OHzkfaRSA7S1vZGNHTeu6D4Vm9PFWP/aSTjXCgUSv1ITi8u1k4suuofu7i/T03srExMPsH3bp/H5LmFs7H84cODtuPKmqysdmLVgtpiOx9eEuKUTcRw1KxObTZa9bO58P60tr6Gr64v09X+DoeEfsqHtrbS0vIqxsd/T13c70dihfNyof6K5+VWzLkrXMwrCI13TZnVOshxIko3GxhfR2PgikslBgsGfMDz8Ew4feU/+vJPm5mtoab4Wh2PjijxzLWC3t7O58/1s7LiRkZFfMjh4J11dtyDLPto3vIWmplesmPOUcwGK4mfb1o+xoe0NZhiOvjsYHPw+bW1voK31dVgsLnK5GENDP6Cv/xuk00Gczm3s3HELDQ2Xn9aeprXGWlsXpGJR1FUKXyFJCu0b3kIgcBUjoZ+TTPaTTA2QSg0wGX4YTaskqBaLC1VtxaY2o9rK0xZUtXnRGrNY/ASPP/5aZIubfXu/g3KagvHpUB1ORnq6gNMXjE6HKCqct+srPLH/TRw+8l5E0bokh22nC13Pkc1OFslXtoKMlZXlj3U9Net9LBYXsuzDavVht2/E670Iq+xDtvoQBZmx8d/TP/Ad+vrvwGZrw99wBX7/FWsaSmUpyOWijIzcTzB4D5PhhwADj+dCtm39BA0Nl5+Ve42rxG0B5HJxTpz4BEPDPywGx3U4lm5ONBcki4zFqqy5xm0lpU3laN9wHfHYcU51fQ4wsNk2cMH538frvXDFn6U6XWvqan6tUIxFtoITiygqbNr0Hurqn8Phwzfx+BOvpb7+eYyN/Q9O57a8ZHPlvYmp9kLsnBju+pWJLzcfUvHT17hNh6o2sWPHv9HW9oZ8CIHP0tV9C4ahYbdvYtu2T9Lof/GqOs9YTZT3s5U0vSre09ZMR8c7aW9/B+HwI6TTw9TVPXvdu76fD5KkEAhcSSBwJanUEFZr3Wmbfp/LsNna2Lnjc2xoe7Npbtr97wwMfIf6uucwMvorcrkINd4ns33bJ6mt/fuzSopfgOpwgGGsiXWBYRgkY9EVt5yZDsVaR2vra2c8O5ebIpnsJ5UaJJnqJ5U000Syh/GJP80gBbJck9fYtaLa8qnajM1mppJkI5ns4/HHXoMgWNi377sLmqYvB6rThZbNmvlVWANJksqe3bfy+OOv59DhG0kke7BYXBh6DsPIohu5ynz+WDeyM/NGDkMvq1c8b15vGDn0/L00LUUuN7v3ZkGQsVp9efJVi92xqXhstZqEzGqtyx/XIorzz2PNza8gm51idPTXhEI/Lzqncjg2F0ncSnoYXg50PcfE5AMEg/cyOvobdD2FzbaBjo7rCTS+aNl7btcLqsRtHkQi+zl46AaSyV42bHgrGzuuX5XJWXE4ivuaVhupWBTF7kCUVseERxAEtm//DLqeRlWb2bTp3atm5qK6XKRiUQzDOCsn+rmQWoE9bnPB497D3110X9GLmGkeuTqkDUranLUyaTXj362OUMLp3Mqe3bcxGX6EUOhn1PmekQ88fHbb+5f3s9MxlVwIgiCctqfO9YjVWGCeq3A6t7D7vK8QieznVNctDA3/iPr6y9iw4c1r7ohmpaGUORpbbeKWS6fRstlVsZxZCIIgIMteZNk7qxdpwzDIZsdJJk0NXTFNDRCLH2V07HcYRqbiGqu1Dl3PAXDB+Xet2sK//Pdarf+RJNnZs+d2Hn/idXR13TJrHUGwFD+iKE87LuRlRMGCIJp5SbQhWMy8IFgqzomiMoOMKdY6ZNmHxeJa8fWRLHtoanopTU0vJZMZY2TkV2Zcx+4v0NX9BVyuXfj9L8TfcPmajY+GYRCLHWY4eC+h0H1kMmNYLB4CgasINL4Yt3vfObNOrBK3edDf/y10Pc35++5c1cCiit1BOpFYtfuXw3QhvLqDvSSp7N79tVV9BpiDsK5pZJLJosnpuYB0PI4gisgLxCJbLiRJZfPmD9Dc/EoUpRFJWp3nQLnzndUnbrlsllwmvWra5AJqvBdR471oVZ+xlihfwKiOtV8IVvG3B7d7N/v2fgtdz55V5pDzoRjaZw2sC1bDydhKQRAEU4NjrcPj2TvjvGHoZDKjJY1dPs3mwrRvuG5VTe7UMo/D6hK9Dy8FFouTC87/AZnM2Kzk7FwhEGCS7paWa2lpuZZUaoiRkf8mGPoZJ09+ipMnP4XHcyF+/xU0NDx/xU1fwYztGAr+lOHgPcTjJxAEmbq6S2lsfDF1vmcsqEE8G1ElbvNgy5aPAqx6QErFbl9Tr5IrtY/lTKMw8JpaxHOHuBVizKz24L4WzjOKgdLXQKOcLjp1WV3idq6h0lTy3Bgbqjg7cK6QNijF3VwL65mik7GzcC4XBBFF8ec9jK78For5UKFxW+V5wvyeq789YD1BVZvM/attbyCR6CE08gtCoZ9z/PhHOX78X6iteQp+/xXU1192WnvLcrk4o6P3Mxy8h8nJPwMGHvc+tm79OP6GyxcMfXS2o0rc5sFqE7YCFIeTVDSyJs9KRSPrUkq3HNic5v8nFYviaVjYzfTZgnQ8Vozvd7ZDLXNOstpYKW+cf2tYK1PJKqo4l1HUuK2BELa4V736vi4JxbWPIKDYzh1h73qE3d5OR/vb6Wh/O7HYsTyJ+xlHjr6fo8c+gs/39/gbrqCu7lmL2u9sGBoTE/9HMHgPI6O/RteT2NQ2OtrfSWPji874vrq1RJW4nQHkMhqRsRRTowmmRpNERjViExP84iv7V/3Z44Pj2Nz20rMMo+K8MefBjKqzVFhkI2ZVJM0snFXhVFaWmDLd+v7hridw1JRNlgu2e7ZK8x7OCWHOg5kFM76PMHvN/iPDGLrE47/tw11nw1Nvw+VTsarr/3U1DINEJGP267EkUyNxQODgH7sI9a1u/05O9QHQ9VgETRvEU2/DXWfDVasgSmf3PrSVhGEYJKNZwiMJpkYSTAyXhEa/+WYXotgHRum9MYqZQplRdo5ixen1zXMz61tk0ezXDTa8DTY89XY8DTbsbus5ZUJUxbkNQzeIhdNERpNMjSUZ6R4H4OGfHeX4I0sXHi2l60dGDgIQ7Erh8Sdx+1bP3P1shJbVmRpNEg4lmAzFCYcShENJRnsKXqitfPdDD+JttOP12/E22Knx2/E22nF6FQSxOg6tJJzOrTidW9nYcQPR6AFCoZ8TGvkFY2O/QxRV6uqeib/hCny+p8+IARyNHSU4/BOCoZ+RyYxgsbgJNL6YxsYX4/Fc8Dc5Z6z/leBZilQ8ay5cR0ufSD6Nh9MVdbU0aJkkscnZ3bOuJHLZBJpmrXjWfB1/wXdCWICcTMOsJGp2ZrVgtWzK7L7JqQiCWLnZeVHv8hLbvpS2LfSd5judTSbQNIn/vftkRbnNJRfJSOHjqVdx19lweNZusikIHgr9OzKWJ2ljKaJjSXJZvVRZAEFUSMViq96/k5EpALr3R+g5eKzUBFHAVauUfrt6G56y1Go7N4fBVDxLOGSSs/BIsiLNpLRiPVEUQJBMJyu6hJ7vnIVxwTwPIBTfEUEw/+SLS+eKVQXKEvNe+XPZtMZYf5Sux0cx9NKLICsSngZTUFEgc94GG54Ge5XUVXFGkMvmx7rCPD5mzuPmmJdCy5WNdZjzejISxaIsfqybd6qY41w8bApbHrpvmId/HsVVq9K0xUvTZi/NW7y462zn/PtiGAaJqQyToYRJzIIJwiMJJkMJomPJit/V7rbi9dtp3t7I8QdM7WjjJg/hUIKjp4bJpkvjoUUW8TTkCZ3fZhI6vwOv34ZiP3dMe88EBEHA7d6N272bzs6bmZr6a57E/ZKRkV8iSU7q659NQ/3zSSS7CQbvJRY7iiDI+HxPJ9B4JT7fpWetB+eVwrm5YlkDFAaNEjFLVAzu6Xiuor7dbcXTYKN1W425YCwsTuptPHxfH3/9xUFe9oGLVnWw1XWNL7wyxe5LO3nqS89+727x8CRfe8tX2fvsBvZedu44i/jmDXfga23huW+5pJIcjZrkaPjUFCceCVVMTJJFxF2nlpE6taitc9fZkJXFexEtaM0KC5Sp/MLFzCdJTFWSZIsi4akzF9ltO2tNUlRog8/GN2+8k6YtDi5/5+r2uSMPJPjll+EVH/l7FHt9URJenp766yipeLbiOtUpl/1WavE389SvLSFeDjLJHOGRRF57lqxIy8cgQQCXT8XTYKexoxFPXsrsaTC1ube97Q4ki8xLbrpgzdquaTrR8ZQ5ZubbPTWaZGwgRvfjY+hlpM5iFfHU2/NEziRzhTHU4a2SuiqWB8MwSMdz+Xk7QWQ0VRozZhGyyoqEu95GTcDBhvPqzD6YFwLZvRa+dO1/suNi36rPrw/d08MD34eXvv9phHriDB0P03twnGMPBgFweJUiiWva7MXrt5+170g2reU1ZokSSQuZY142NY1w+e00tLnYcpEfr99OTaMdT4MdJS+cmxga4PgD4Kmr4blv2AmU5rtwMH//EfP+swmXbC7ZvK/fjiefev123PU2pKpVx5IgCCJe74V4vReyefOHCIcfIhT6OSOjvyIYvBcAt3svW7Z8FH/DC866+KiriSpxmweaphObKCwskhUDemS0UrNQLtXvvMCfX1QsbuGs2B1ouRzRsVEkuVKiY5SvzsvyBiXzpVnrVpwwk6Kb+XNkj1vJ1Xx01Z+Vy2bJJOLY3J5VnwDTiTiq04nqkFEdMg0bZu61LO+bkWnEavhkuEKjAmBzW/FUEDuTpGRTmtmv8xLkqdHkrFozp1fBXWejbaev4j6eehuqU573N1EcTmKTE4RDwYryykumaz/nsCOdp25kdMT8rk4nDq+Kq1aleevMYNzpRLb4XQu/WWQ0Sah7ipN/GamYqCsIcdkizVWrYpFFU4skCAhiPi3PF1NTG1VMy8sW0ZeyaY2pUdPUp2DeWCBnyWglCXXWKHga7HSe34DXby5avA023D4bkjz3wkJxOLHIaytNliQRb4NJINnpqzinazrRibT5XUfz33s0yfhQnO79Y+haGamTxbymzl7U2Hkb7Lh8agXpNgxj2ngJ5WacxSG1fJw1ysqZ/fpKlJ43l2m0UMrMWXdGvyjTXE7vSzP7YFl5eZ+bVn8lUPhNDcP8HUvHZWW6Uaxr6GWmtPr0OWueZ1QULKZd0451g9hk2TtfmMfHUmSS04SsHiueehst22oqhDjuOhs21/xjndVmJzY5QTw8ufjvM0uDjQVs9yNjI1gUBX9HLf6OWnZf2ophGEwOJxg6McngiTCDxyY58Yi5ncDuttK02SRxTVu81AYc64rIaTmd2GTaJE3BEnkKhxLEJsvIswCuGhVvo51tmwJF4uT1L87EsbD2Kd8HLQgCDo+Cw6PMmC+0nE5kLMlksEQWw6EE3fvHKsZeQRRw16kzCF2FpYBQ/p6XrBfK320zLRUWrBjKz5eXzzuWCAJlj6tAeZsqTpePUdPblz80AHSzjxbGx+njgDlUmu87zBwXYNq4YIBo7KOxZi/1nvcRi/8Fq9yIam0HAWLjIAil7TCzrQ9m/W1n1Jk5PksWEZvr7IrBWSVu8+C33zjMyb+MFI8tsog7P4C37jA1C576/ELOpy5b4lIIevv1d7x+Rdq9EBzemYvZsxEWWUZWVFLxlSFumWSCcChIODRMODhMODTMVGiYyeAw0fExMAwsVgVPgx9vYwCvvxGPP4DXb+bd9X4ky+m/Uql4bMEYM5Ik5jW2MzdYF6XIYyUzxoLWafjkTG0dLKw1m2/RvxDsHi89j/+FO971xmXfY7EQRHFBN8+KXaa+Taa+baYAo0CIKyTv+d9w6GS4QsK7cm0uJ3SVi3OAdGLmwtLbYKd9d12R+BQIi8W6vPiMzppaZGX9mJ+IklgUfE2HrpmLvKKGMb8InwzG6Tk4hp5b7A7Vv2FMI3OCAEwjeYaeJ14A+nRiZswYQ84WiJJQHNsCGz1FC5iCcEZe5jsEYHO7OfC7+znwu/tXsMWzY7pDLkEQqG1yUNvkYNfTWzAMg6mRJIPHJxk6EWboRLi4nlGdskniOk0iV9fsXDXLAi2rEwuniYdTxCbTZZ/8cThNMjItrpvNYpo2bqkpEjNzL9ryxzgoOWJabMgYySJS0+igpnHmfJyKZysIZuHTf3QSrVzwWcUyIACh/Gd14e9wc/X71ta76emiStzmwfaLA+YiNm+SY3dbV2Vw2/bUSwDQtdKicC5txOyaiIXOlyQzktXKpgtWLybdWkN1uUhGF0fcDMMgGZkyiVkoSDg4VEHUCnukCrC5PXj9jbRs24nHH8DmchEZDeWvHaZ3/+PkMiVpoCCIuOrq8fob8foDePyNeYJnEjvrIrxY5TIZM7DqabgqFgQB1SmjOmX87bNo63I60YkU0bEUsiotSmt2OnjW69/G0LHDxeO5pOwzJeuzaJjNgzmv8dT7kSzL1xyVE+LWWdqXimeZGk0Sm0ija3pRo1CuXago0ys1DZX5ymsxDPSCFkLH3GumG9g9Sl57Zi4wV8NJzfOu+ycE8eww9RElsajxbd1RaT6jFzQrI0miEymzr8yQRldKs8v35JWXmzWFaddX7t0rl3rP1kdndum5NSnTrShm2zdrUKapMqb3o2nl5X0u37+m1y2Wl/fJggS8qJ0rCRUK0mxBLO1ZLAgemEWrN/vxzLoLYebQNF3rPttFlVmHV8Fdb8NZo5r7NlcBl7/jPYz0dM1sygLtN+vMrmWdq6BhQ8e8bREEoUh4dl7SjGEYRMZSDJ2YZOh4mMETYboeGwVAsVsIdJb2yNW1OBfl0CmX1YiHK8lYPE/GCsfTrQLAJGbOGgVnjUJ9qxNHjYqzRsHbYMPrdyyo2VwuREnCarOviOdh1SHT2OGhsaPSrb2hG0QnU4RDCVKxbJlGP69hyv8p19iXa/1naPzLr60YG6Y7gSprw6z3KCQzrbUWuqb8WcK0caEwBgr57jL9fYeSELJyPJhpASCIM8fc4u8y3/g47betPG/MUr/0nc82bRtUidu8aNvhW7jSCsBqs7P7WZetybPONahOV4WppK5rxMbH8+SspDkLh4JMhYbJJJOliwUBV20d3sYAnRc+CY8/QE1joKhFWyg2nGEYxCcnKu5fIILHH/6/GSEe7B6vSebyRM4kd2be7vEiCEIxnt9qxpiRLGUmamsA87s2rsmzVhOCIGBzWrE5rTD/mumsg7vu3Ig3JIoCbp+t6mWvijOCpi3baNqy7Uw3Y1YIglDUYm9/ahMA0YmUqY07bppX9uwfA0BWJQKbTBLna3GSimbKyFieoIXTs5IyxW6SModXpb7NVSRoTq+Ks1bB4VXOqIfkS1/7Zurb2lft/kJ1DKpilVElblWc1bA5XQRPneAnn/4o4VCQyEgQLVcyLRMli2namNecFc0bGwN46v1YrMuXtgiCgLPWh7PWR8v2XTPOpxPxPHEMFs0uw6EgA0cOcuSBP1SIgGRFxetvxOYxA0eq1VhkVVRRRRVVrCJctSpbn9TI1ieZgrV4OM3QCVMbN3R8kj/fM15RX3FYTAJWo+BvdxcJmrNWwek986RsMdj1jGef6SZUUcVpYX2/YVVUsQACm7cSPHWc2MQ4dS1tdF74pKKZYk1jE06fD1Fcvk386UCxO/Bv7MS/sXPGuVw2mze7HCYcLGjrTGJn93ipW0WJYBVVVFFFFVVMh8OrsPkiP5svMvfPJSIZwqE4dreCo0Y5rf1/VVRRxcpAWIxXp7XAhRdeaDz66KNnuhlVVFFFFVVUUUUVVVRRRRVnBIIg/MUwjFm9ppwdu9GrqKKKKqqooooqqqiiiir+hlElblVUUUUVVVRRRRVVVFFFFesc1T1uVVQxBwzdwMho6MkcejIHuoHkVRAdq+c6v4qlwdB09JSGkcqhpzXQDASbBTH/Wa3YRFVUUcX6hmEYGFndHBsyOpLbiljdo1VFFVWc5agStyrOWRQn7mQOPWWSLz1lEjEjWTjOlY6n10nlZsQ6ARAUCUutiqVWRfKpWGpt5rFPRfIqCMsMxP63BMMwMDJ6kXDpqRxGqixN50qErIyYlZ83UhrGfIFOBRBUC6I9T+Tscj5dIK9aEKRzk/AZhoGRzKHFsuixjJlGM2hx06235FaQXFZzkeu2Ijnlan+uYs1RFJqVjQvl48H0ccA8Xygr1MtB+fAggFSjIjfYsfjtyA12ZL8dS70dUakSuirWD8z5UZvZ55PT+n/KXKcYmmGO214FyWNF8ijmWO62IljOjvHb0A30RBY9lkWLZhCskvldXNbqHDQNVeI2D5KHx8kG4/NXWknfLpKAYBERJMHsqGXHlJdbzHRGeXl9STirtUKGpmOk85NwRVo2ORfLc0WtmJ7SKkgZ2vz/IMEqmgv1vIZGcivIfguCKhW1NqJqpggCuckU2kSK3ESK7GiC5LEJyJU9QwTJqxaJncWnItXmyZ1PRTzDrpIrpNApDSOng2aYv7dmmHndgJxuLp40A8rPTcubaT6vGxg5M2j09Hrlz9RT5v9swXdHAMEqIaqSScDUPLGqNX9HQZUQlXyqWszFlySYz0hk0RM5M03mzHwyR248iZ6Ym5QXH61Kc5M7m4xot5hts4oIVin/MfOinC9bownT0Az0eBYtljEnvWJaRs6KaRb02aQRhZvNLBftMpIrT+TypE7K50VXqexsWSBUsfowcnpJKJbSysbnXFEoVjFmp0uL0MLxghDJjwPmuy+oEpJXQZ5lbBBkEW0yRXYkQW4kQerEZMXcINUo0widA0uDDVFZP0skI6ujRTNo0Qx6NIOh6YjO/PvnlBFslrN6zp8PhcDy5APGF4LJUyjXpx3ng8pXHOfrzYxszxwR3Jk/OHzZNRXVyg7M92AWgUO5oGF6PrnI+VEUinOjIAqkjk1iZGa+N6JTNomcp4zUeRQsZQRPkFdv7NYzmikcjGbQovm5KJpBi2SKJE2PmvPTXHOT6Mh/h8Lc485/l7JUUKVztv9Px/oZldYhkgfHSPx15Ew3Y/nIEzrBIpTl8wQvT/JmlC9EECuuEdAMjUw6SSaVIJWKk0pGScVjJBNRJFFClR1YZTtWi4osqciCjISMZEgImoCR0UtkLFOYwDXIzaNJKYdFRCyQrDzBMhf2JeIlqJUETLBZiudPV5Jj6IY5CI2nyE0kyU2kyI2b5C55aAw9nquoL9otJpHz2Upau/yx5LbOadpnGAbkjJmaqPR0jdTMsuKkkSe5LPKnXRACIJb1sXweEZAEMxXNVFQsSLU25MJCqpAqlceiKiEo+dQqrZqpo6EbGKkcWhm5M/J5LZGXbJaRvuxEqmQyu1hhjSQgyOXkrkTyRFlEUMoInywhVtQpkUA9rZUIWTSLFs8WJzo9nkFPzNEmi4DktJoTt1tBbnIiOWVzseeUzfL8edEugwF63JxQtUhpgVjIa9EMuWAcLZaZtQ+JdksFkTOJnUxGSDMVG2FstJ/g8ClikXEcHi8OTw0OTy0Odw0Ojxe7w4Pd5UV1OBEFaaZQYLrAYLpgYZZjs/+Z411FKgogiQgiIIr543z5nPWFmfXKjwWzDIGzfgFhaEaJSBUJlzbNMqHcckGrKJtXEw4gCcUxufDuy05bXkAjFdNZBTT5MkEWl/07G5phjtehBNlQokToToUrBHGSR6nUzuXzKyWAMwwDI62VFrLR0ruml713WiRrCpvmg5R/313me114/8rLzPdTNseYVe6jRk43x9N4fixNZNEL+XhJsFYcgxN5Qet0UlZIzyUUrEGKfdySFzo4Sv3cVurzWAVyeoZ0Lkk6GyeeijA2McbE5ASTUxHSmQzuZgc+j48GVz01qg/VsGHJWSCuk5tKkxtPku6amrUfiQ5LngRVkrvyfLmZsaHnhYXRTCUpi2bQYpWkbFYhjEBe6GAKBeWAoyiAEPOpntXRpzJokbQ5B02l0cJpMn2RGesqAEEWK8idWMyXkTzXuWFBUg0HMA8MrSDiWQiLGAAXqmIYM7UaOTOt0IrkSgsTQ9MhN0v9Yr2yRU7FvQr1pj/DzOtZDSOrFa9BNxD0lRvkc3qGrJ4hZ2TQyKGLOrpkmGIEq4ioiPmBy4rFriA7VWSXDavbjup1oXhdyA7FXPiu85dQT+XITeS1dNPJXThVuQCWBJPIeRWMnFEiYPl0Ie0hABahqH0SylNVQlAkkAWSqSjRyDhTkyHSmQS6oaHpGrqeRdNzaHoOXdfQ9CyaliWn58xUy6FpGXKaWa5pOXQth57T0HUNPadhGHMs2ASBmsYAdW3t1Ld1ULfBTD31DQji+v4flqNA+PSkuW/GyGhlH90UbHzrgQAAIABJREFUPhTKs+VlpfLZ6iy40M1DUCRzQeaQi5Oc6JCRXDKiw5wIC8RMUFZncVY+aRcXmJEMuUiK1EiEzGQcI64hZSXEWfxf6egIBgjC2fN/XzIKQo0ioaNI9hAEkzAKZeQvf1ysIwqmQL9QXxIqtaK6YQpz8lqFCm2CXtBQlOdL50uaiHxeL9dK5O85m+R72vcrCcEKgjGpZJpcJiwr7jktCMtUC5lsivjkBMlYBKtqQ3U4URxOrKp6RscDQzPITaZMQjeSIBeKkx1JkB1JVggTJbe1SOIsflNDJ9fbTAEIJbOv4mK2XBAy7XjWd98imAvZ/Keo7S7knVZTcFowdS7XZMRKC2g9lp3d3F8Wiwvk8gV0IW+eM4U6gixiZPVK4lWW18pImJ7IFUnZbNqfAnRRJyfmyBopUrkEyXSUZCYCooBklZGsVmSrFclqxaIoyIqCRTVTWVWwqCqyTUVWFARRMolQXmiCUCY8Eacdl50v/dOZ/WC+V2CuatPW04IklKxF8iRMt0A6EycVi5KMRkhGI6SipXwyGjHPRSLEY1Fi6TRpHXSran4UFd2qQPn4aeiVx5qGmEkhZlLIWg6bbMFlt+F1u3F7fLhstTisXmyiA6thw5K1IKYEjFgObSptkuhpEGwWk1ClcnP3q8L85CrrU+X92CkX56/TEcoWtc+RNNrUHGkkM3PNJFAUZBYInhxw4Hxy07LbslqYLxxAlbjNg/2//RXDJ49hVW1Y7XasNjuKzY7VNsuxzTyWLOtDiWnoOrlMhmwmTS6dJptOk8ukyaSSJCNTxKfCJKbCJMLhfH6SxJSZz6XTs97T5vTg9NTidNdgd3mxu73YnR5sdjc2hwub3Ylic6IoDkTB1OIZFoOsliadTZHOxM0BKxEjFYuRikdJxaL5fCyfN4/T8fjcJACQFRXF6cTmcKI4ncWJX3U4UBxOFLsT1elEsTtQHaW84nRika3rQiJuaAZa2DS7LHy08SS5cBrBIlZqovKmQBVaKqVcS5UvKzNXy6ZTjPb2MNJ9ilD3KUa6TzHW34uumYOyxeHC7nRhkURESUKULIgWCVGUylILoijmz5l5yWJBECUkS/4aKX9ekkr3KebN48RUmLG+Hkb7ugmHgsUJTlZt1LVtoL6C0LWj2B1n5H8yHdlUiqmRIFOjIaZCQaZGQoRHgsQmxsEAQRQRRRGh+BHyx1LlOWF6vcpjURARBQsSEhIWJCyIuoQkSFicNmx1bhz+WhwNPpzeWmRVPaO/SzqRYLSvm9GeLkZ6uhnt7WKsvxcta+6Vs8hW6lo3EGjbQr2/g9qaAE5bLdlohmQ8gdvuQhAFDMEgk0mRTadIpxOm5j4ZI5WMk0pEScWjJONREtEpcloG3dAxDA0dHd3QEC0SisuF6nFhc7uxeT3YvR7sNTXYvR5kWUGSLEiSjGSRkUQLkmRBFCxYLBZEQUYUxSJZMfS8YEwvMxsupAWNnj73cdFkq5gvESEznydTRZKVv9agdI/y/LR7VCxMCwvVArmbNU+eBE7Li9PvkyeXQv56i1CyVJhOwGzSnBobQ9dJRiNEJ8aJTYwRmxgnOj5uphNjxMbHiE2Ok0kmZ+1XgiCi2O0oDgeK3YnicOTHdoc5fufLi+O8w4FqL+VlRV01YYU2mSpp58q0dOXES3RZEQTmNPsSFGlWM+OidixftlJmjxUEMlYgiwXtvUnytGgGPZaZVYsBmNYT8wgNBUXEUAR0i06ODBkjRSobJ5GOEEuEicTGSKamSGsJ0nqKjJZER8PmcuP01eGq9WGrqUWyO5F0jUwsSiIyZZKYfDpXf0EQUJ0u7C63+f67PNjcbuxuDzaXG1s+LR27kZXS2GkYBlouh57Lkstm0XM5tFwWLZdDy05Ly8r1XJZcLouWnf/aTCpJqkDI8mQsk0xU/o8Aw2JFV1SwOxEcLnSrSk6ykCtjmIIALrsdr8eDz+fD72+gsbmFxkATiqIQnpxkqK+X4PAwoyMjTITDRGJxUvkxOf+FEbUcQiphErt0qkjwhFwWq6Ji93pxuX14XA24bT7sVg82yYViqFg0Cygi2ESwCaAIGHYBQxEwFAMkwVy35YVABvnxLZ+a58Aw9LzsqKxu0QTW/EiShMWqIFllLLKCxSpjsSpYrFYsshWL1YqUT0Vp5nhkGHkBY8GCZCpdkep5cmfxO2h4y+45+/eZQpW4LRN/+O4dHPvzn8gkEmRSydlto6fBIlvzpM5WJHayzZYneHas9mlkz27HqtqwWBW0bKZIsLLpPOHKTEvLz2fSZFOpGXVy6TS5bGbhLygI2N0e7B4vdo/XNFcq5L01pXNek6QtREqTySThcJipqSmmpqZQFAWfz0ddXR02m22xPztgLgDSyYRJ6gqELh6b8zidiJOKm4Qvm5pjkM9DsljyJK98YVBJ/CrO2R2oTieq04XVZl8XpG860okEoz1deYJ2klD3KSYGB4rk1+Zy09Cxidq2dpKKg6HJKQaHhwHwer00NDTg9/uLqc/nQ5JWZ8N+JpVkvL/PXPj39jDW38NobzfpeGk/qauu3iRzGzqKWrqaQBPiCrdJ1zSi46OE86QsMhoiHAoSGQkxNRoiMRWuqC8rKg5/ANFTiyIJKIaRn4QMDF3H0HV0XcfQtbK8Xpk39LnPTauna+Z9pkOxO3B4a3DW1uKo8eGsqcVZU8o7ampx1NQgW5XT+n0MwyA2Oc5oTzcjPV2M9JxitKebcGi4WMfmclPfvpGGsk9NoLn4v4pGoxw/fpyjR4/S1dWFpmk0Nzezd+9edu3ataixwTAM0vE48fAE8fAk8UkzjYUnSYQn8+Vh4pMTpOKxJX9PSTaJnbkYkLHIMpJszZdVnivmC+dka1FApOSFRKawyIXqdK7bMWOp0HI54uGJIhGLTYyZBC1PxqLj48Qnx9FylQRAEEQcNTW4autw1vpw+nw4a3w4amrJChKqRSKbSpCOx81xPBYjnYiTjhfSOKlEnHQsRjadmreNoiRVELwSsXNgtTtMUmg3SaA5F5tl1mK5HckiL/o3MXQDLZyuIHNASWtVQcxWz6ulURiHdKM0xhTHJKM45hTLjLJ6uoGu6+g5DRI5tHgOI5bDSGim+XgyR0ZPkcxESaQiRBMTRKJjTIWDTI4Po2nZirYIooizxoeztrbsf16H6vGiy1ayiCQy2f/f3r3FNpLl5wH/TpEUKZGUSFGX1l1qdU+rZ0bd6sUm2YHXm8kmzsLIW2LEyMsGNgIHBmIgQJw4QBAEzu0hRp7y4GABOzDyEGfhhwRGLmMgjmMngRfY3VaPpjfStDTdat1ad4niRSSLdfJQVYdVxSJFqUWxWv39AKKuJIt1Oef8zzlVxMnpKY6OjnB0dIRsNgsAiEajmJmZwezsLGZnZ9Hf3w8A0MtlFHNZFLPW6+wUhWzWFdzZQzvo80s3ASDcFYXQNBhWkHXd7DQiFA4jEouZAWOyF13xBNDdAz3chZIUKOo6zornyOby0B3bEY1GMTg4iIGBAdcrnU5fKU8ul8s4PDzE4eEhDg4O1Ovw8BAVR1AX0jR0h0PogoFQpQQU8tCzx6gcH0IEJE5oRAjNTJO7zEAu4gjqvEGePW2/ejPDePQz3+n0T6jDwO0aSMNApXSOcrGIUrGAcrGAcqGIcrHgmDbHK+dFlArWPNf6BZQKBdXicRmhSASRrmit24A97hhGYjGEu2rLI1HPOtZ8OyDr7u2FprWWEEgpkc/nVWB2cnLiGj89PUWpQUsdAPT09GBgYEAFcvbwqolRM1VdVxm/HcyZwxzO81aBwJpnLy/lc2bhIJ9rmOADZqIfT6cRT/UjkUqbBWRrqKbT/ehOJNvW5ad4lsXey6+w+3IVey/XsPdqDcc722p5It2PoZlZDM3cw/DMLNLjk9g+OMTS0hJWV1dhGAYymQzm5+ehaRp2d3ext7eHg4MD2OmBpmkYGBhwBXNDQ0Po6+trT422lMgdHdaCuddmMHe0vamORygSQWZ8EoOTMxicmjYDuqkZ9PT2Nf3cYvZUtZRl96zAbN8K1A72XcdbaBp6BwbRN3QHfUPDaihjPXhzcoq1l6+wubmp1o9GoxgbG8P4+Lh69fT0XOt+KRXyyB8fIXd0hNzxIXLHR+b08SHyx8fWdH2BGQBi8YR5bvbXAjrnMJHOoCeVRjgSgVGt4mh702xFWzcDtf1XX6F4llWfl7ozgqGpuypQG5yeQSKdqTsnDg8Psby8jOXlZWxsbAAA0uk05ubmEI/H8fnnn2Nvbw+hUAhzc3N4/PgxZmdnryUt0CsVqwfBKfRyCdWKDr1SRrVSRrVi1o6bQ8e0XkG1XEZVr0Av15ZVK7V55tCatj6jWilDL5dhVBt3CxNCs3oFxM1gTgV45rg93+xBkFQ9CGKJhFnIvOT1JqWEUa3C0HWrVcB6OVsD7Glna4JjX5QLBavVrNZylj89qau8DHdF6wroiXQGyUwGif4Mkv0D6EmlXPnM/v4+nj59imfPniGfzyMcDmN8fBxTU1OYnJzE+Pg4olH/CgeVtlsBnUrbC7la4JevBX0qfbfe06g3ies3WZWvdiDX1d1TC/QcwZ+a7o6jq6dbBYSAGWiYrxL0SsUcOueVzfOx4jPPu55eLkP3mV/VdRWgtVKpfB3CXVHz2KYzqrXMPu7JdAZdyV4UdR0nJ7Wg7OjoCIeHh8jl3BUq8Xgc/f396pVIJLC9vY3V1VWcnp4CMNMMO4ibnp5uuQLYTjdrwZwZ7BWtYE8aVYTCEWhhs5JGC4dVsBWKRKzgyzOvbtpcTwuHEQ6bQy0UgpQSBwcH2N7exu7urgqUjo+PXduYSqXqgrOBgQHE4/EbqeiRUiKbzfoGdPb+t/Umk+hLJhCPRhHt6kIkHEYkEkEkEkZXJIKuSASRSARdXRF0RbqsZWZvBiGEKgs5h0KIWgu/emmqx0BVr1rpd8V9HVnDatlxXXmXOa8569qpqnH39Thy/wH+xj/7jbbv78ti4BYweqWigjo7oKuUS3UBlh14hbu6Wg6wrsowDJydnTUNzHRPwTAajSKVSiGVSqGvr8813tfXh1Kp5EoM7GHe0bKiaRrS6XRdQJfJZG4sAXOSUqJyXlStec7Mv3iWrdX2Hx8hZ417uz4AgBYKoyeVMgvJqX4krGBPBX1WwNfTl2raipQ/OTYDtK+s7o6v1pDdrz0wp3dwGMMzsxiamVXDeCqNarWKtbU1LC0tYXl5GZVKBclkEvPz85ifn8edO3fq9q2u6zg4OMDe3p4K5nZ3d1VtKGAe86GhoboWusu2qLZKr1RwtLVhdbM0g7mD16+QP6llgvFUWgVx8VQaZwf7Kkg73dutq6Xv6Uu5grLacBjJzKDKfLe3t1Xwsb+/DwAYGRnBw4cPMT09jaOjI2xubmJzcxO7u7sq6M1kMiqIm5iYwODgYNtaL21SSpznzswg7sgM7nLHR8ifmAFf3jHtF2R0J3tROT9XLfWhcNjap3cxND2Dwem7GJycQbRBUGoYBnZ2dnz319zcHObm5jA0NKTOOSkldnZ2sLi4iKWlJRSLRSQSCTx69AgLCwsYGhpq0566flJK6OWSmU7kcu6u31aFUTFnVRypngJnZoCRyzXtEh4Kh82gzuoFoIVCVpDlCLZ0q5tWpTZ9HQX5WDxhBmL9mVoBvd8qrFvzY/FES2l0qVTC8+fP8eMf/xibm5vQNA0ffPAB7t+/j729Payvr6trSAiBkZERFchNTk4iHr+ertNVXTcrWwsFlAp5lAt5NW5XtprzrXne6ULhwh4dV6FaBbqcrQJRV8uAe54ZdNS6YpuFXuEoKNfN14Tqsm3fT6lpoVqhWfO8X5jvCYUjiKfN4Dwaj6NUKtUFZfa4M28HgEQi4QrOnK9Yg+7eUkocHR1hbW0Na2trePnyJcrlMoQQGB8fV4Hc6Oho29PVi0gpcXp6iq2tLWxtbWF7exvb29sol810NBwOqzKN85XJZNDV1dXRbW/Gr5XOPs7NKui9urq6EI1GfYfNlkWjUbMba7UKXdevNGx13ZGREXz3u99t4968GgZuV/TZZ5/hyy+/RHd3N3p6eloaRiKtd7NoN8MwUC6XUSqV1LBUKiGbzdYFZtlsFoanpSkej6uAzBuYpVKphgnvRYrFoiuQs4eHh4eoOgqVsVjMlejZ4/39/QgH5F5CwLyXLH98jNzJEfLHVrctuyuXI8g7d7Rc2ITQ0N3b62ixyyAaj+N4exO7L9eQPz5S66ZHxlwB2tDMLLoTSbXcMAxsbGxgaWkJz58/R7FYRCwWw0cffYT5+XlMTk6amfYlFYtF7O3tqZcd1J2f1wKiZDKpAjk7mBsYGGjb9VA4PcH+a7tlzrx37nDzNaqVCiLRGPqGrWBscLg2PnQHfYPDDe8Pq1arWF9fV8FHNpuFEAJTU1N4+PAhHjx4gFQq5fveUqmE7e1tFchtbGygUDAD+kgkolrlJiYmMDY2hkQi0Zb9chH7HqScq8XObFmJRKMYmp7F4PRd9I+OX9g1Wtd1vHr1CisrK1heXsbZ2RmEEJiensbc3FzT/eX9nBcvXmBxcREvXryAYRgYHR3F48ePMT8/f60tmNelWq1iZ2cH6+vr2N7eRiaTwdzcHEZGRi5V2SQNw7wPJpdzdf+2ews4A71SPgfDMHxr/cPWuBYOq/G6lgM1ffH7I7GY616gq5BS4vXr13j69CmeP3+OSqWCgYEBPHnyBI8fP667Bs7Pz7GxsYHXr19jfX0dW1tbKj8YHBzE5OSkCuZaOa/axTCqZqWrCuasoM8aAnAEXFGf7llRd5AWjgTmAU26riOfzyOXy6lhNpt1BWp2umZLJpMNg7NGLaeXUa1Wsbm5qQK5ra0tAGYl4t27d3H37l1Xt8p2yufzKkCzgzV7f4RCIQwPD2NsbAxjY2MYHR3FwMDAlfLcILPLlc6ypbeceZmht0HgsoQQ5v1w4TBCoZBrvJVhf38/Pvnkk2vaO9eHgdsV/fCHP8TLly9RKBRQLBbV0Nkv2CscDrcc5NnDWCwGTdPM1p5K5coXgHfYbDsBoLe31zcgs1vMbrpGyDAMnJyc+AZ1Z2dnaj0hBFKplKu7ZW9vr3rF4/FAJpZVvWK12DUJ8qwAzxukDU7dbdjasbu7i6WlJSwtLeH09BThcBhzc3OYn5/H7OxsW4Jcu5uFN5jb399XhS0hBDKZjArm7Fc7uscC5v1qpUIesUSy5cJzuVzG2toalpeX8eWXX6JYLCIcDmN2dhYPHz7EBx98cKXAQUqJ4+NjVyC3u7urKkfS6bSrVW54eLjjtcetKJVKePHiBZaXl/HixQuUSiVEIhHcu3cPc3NzuH///lsFWrlcDktLS1hcXMTu7i40TcODBw+wsLCAe/fudWwfVSoVbG5uYn19Hevr69jc3FTpa29vr2qV7u3tVUHr9PT0O3FMr1s2m8WzZ8/w9OlTHB0doaurCx9//DGePHmC8fHxlq/NSqWC7e1tFchtbGyo2v6+vj5XIDc4OHgr7iNsB8MwUCgUXMFYo1exwUNAent7XQFZJpNBf38/0un0jZcTCoUCXr58ibW1Nayurqprz9mtcmZm5soVy7ZSqYSdnR1XoHZyUrvneXBwUAVoY2NjGB4eDlSF8ruiWq36BoHegKzR8LamsQzcrlmlUnEFco2G3vFG+1oIgUgkgkql0nAdr0gk0rSZudEwGo0imUyit7f3nUpkSqVSw1Y6b4CqaRqSyaT6nc6XPS+ZTL5Tv9/r+PgYX3zxBZaWlrC3twchBGZnZ/Ho0SM8ePDgWmo6r6JareLo6EgFcnZQ5+zfHwqFMDAwoAK5wcFBDA0NIZVK3UjAXSgU1MMyVldXoes6YrEYHjx4gLm5OczOzralMFIul7Gzs6MCuc3NTXXfRzgcxujoqArkxsfHkUwmL/jEm3F2dqZa1V6+fIlqtYqenh61v+7evduWltWdnR08e/YMn3/+OQqFAuLxOObn57GwsIA7d+5c+/c5nZ+fq4Dh9evX2NraUkH38PAwpqamVNCQTCaRz+fVObW2tqbOqfv37+PBgwe4d+/eWxckg8xuNX369ClevHgBKSWmpqbw5MkTfPjhh9dyPRmGgd3dXXVM1tfXVde8np4e1a1yamoKd+7cubUFOsDqGn1+3lIwls/nfcsV4XAYiUTiwlc8Hg9UTyInKSUODw9d3Sorlcqlu1Xquo7d3V1XS5rznu9UKqUCtLGxMYyMjHQsj6X3AwO3ADAMA6VSqWGQVy6XLwzGnH2Dg9ii1Al2bWI2m3W9zs7OXNN+rY/xeLwuoPMGeUFKnHO5HH7yk59gaWlJPfBhYmIC8/Pz+Oijj67tPpB2KJfL6v45+7W/v++6CToSiWBwcFAFcvart7f3rWvTT09PVRfIV69eQUqpWkfm5uYwNTV14wU9+/4IZ6vczs6OChD6+vowPj6Ovr4+xGIxRKNRxGIx3/FoNHqtacLBwYHaX/bDWOyHi8zNzWFiYuLG0qBqtaq6Un755ZcwDAN37tzBwsIC5ufnr+W8z+VyqjXt9evXePPmDQCzEmh0dFQFahMTExfez1kul/HVV19heXkZKysrKBaLCIVCmJmZUa1xQQnK39be3p560EihUEAikcDCwgKePHmCTCbT1u+274VyHje7gigSiWBiYkIFcuPj4x0PPqSU0HVd3bJgv5y3MbQ6r1wu+wZjmqa5Aq5mAVlXVzD+Fuc66bru6la5vW0+tCsWi7meVqnruuu+tDdv3qieIj09Pa7ujmNjY4HOW+l2YuBG7zW7dtIvoHPO8+smEo1GXYGcXVi2u7j6jYfD1/MfPIDZ0ri8vIylpSWsra1BSomhoSHMz8/j448/Rjqdvpbv6ZTz83Ps7++rQM4O6pxPILMfj+xsnRsaGkIi0fjBCFJK7O/vq+DDzsAHBgbw8OFDzM3NYXR0NHAFl0qlgjdv3qhAbmtrC/l8vqX7AOwArlFw5zfunN7b21P76+DgAEDjh4t0Sj6fxxdffIHFxUXs7OxA0zTcv38fCwsLuH//fkut6FJKnJycuAr8h4eHAMxWiImJCdcTDt+mtaharWJjY0O1WNqBxdjYmAri3rVufufn5+pBI1tbW6o765MnT67tyaBXlc1mXS2lu7u7AGq9Wuyn3DmHfvOaLbtonh2c+QVfrZS3hBCuylpnpa1zOhaL1QVj9m0XZMrn86pb5dramutBW4D58IyRkRFXoJZKpd6p65FuJwZuRC0ol8uuwM4b5Nn3AFx072AoFKoL6C4K9pyFaMMwsLq6iqWlJaysrEDXdfT19aknQg4PD9/QHumcQqHgCuTsceeN8d3d3a5Azn56o11Itgvj4+PjKvgYGBjo1E96K7qu4/z8HKVSCefn503HGy1rtdB42YeLdMru7i4WFxfx+eefI5/Po6enx9WV0vkEy/39fVcXO7sAF4vFXF3sRkZG2taFWkqJvb09dX7alQn9/f1qf99kS+ZlSCmxvr6uHjSi6zoGBwfx5MkTPHr0qGMP27lIsVhUXV3L5bL5H4lSuoZ+85otu2j9cDjcMNjym+edjkQiDBzawH5M/8uXL9UDo27jw0PodmDgRnSNqtWqKhQXi8VLjbdSgA6FQuo+IvuJkBMTE8zMYXZpcwZ0dlDnfMKlpmmYnp5WT4Ls7e3t4BYHg5RStQA0Cu6SyeRbP1ykE+y/vlhcXMTKygqq1SqGhobwwQcf4ODgAOvr66o1PZFIqNa0qakpDA0Ndazgls1mXfcOGoZxI/cOXnYbFxcXsbi4iKOjI0SjUfWgkbGxMaZJRERtwMCNKCCklK4Cs1+Ap+s6ZmZmcPfu3Vt9g/11kVLi7OwMe3t7KJfLmJmZadv/ylGwFQoFfPHFF3j27Bm2traQTqdVkDY1NYX+/v5ABhvn5+dYXV2te1rn7Oyselrndd9nY/9PkmEY6n+P7PGdnR08ffoUq6ur6kEjX/va1/Dw4cNA//8UEdFtwMCNiIjeK+Vy+Z0MMnRdd/2foP3/eJOTkxgYGKgLthoFXxdNe/+30yuZTGJhYQELCwttf9AIERHVMHAjIiJ6x0gpsb29jZWVFaysrCCXyyEUCkHTNPUfRtc9rWkaent7MTMzw/t/iIg6oFng9u7+kRUREdEtJoRQT7z79re/3enNISKiDmN1GhERERERUcAxcCMiIiIiIgo4Bm5EREREREQBx3vcmii9OkX1pASEBERIgwhr5nhYs14CCJlDEdIgQgKwl2nBe+Q03U5SSqAqIasSqBqQVQlZNQDdHJrzrXHdmraWQQjzXA0J8/zVzKEIaWocIXsdzbWOaxjAR6xfhjQkpG4A1v6RFcPaX9KaZ+07x/TVXH4/qXTFPkZhzUqPasdEhDXXerfhmDhJWTtnvcfBPFaO4+c876/gSnvtJnZ1k5/T9Jc2egDZZXaP9/d5zq26n99sf1xq5euj0rKQIx8P+eTh3mXMyy9NGlZepEsrz7GuWec83TDzJce4ylNUeqcB3mMTqi97QRNtO07mb3HmpbU0xs536/Nba2gE4+F/vq6SLATkYYbXSYtH0P2gv9ObcSkM3JrI/+ANCk/3rvZmDVYG4cgUwo4EKazVZRgSqF019gXimZbe5d51pHOxdCzz2UZhvSDMfFigliHbaaAQtTxaCNd8ez3R4H217fPZVsf2ykbLGs3zfOSFiUkraY33M1p5jzOfaFZIbrSo2XsM6QiyjPqgrCpdmUfHeYO5kIDQtFrQpwkIDbVzyBoKYS6zz0VhL9dE7dxzvEeoZZ7PcJyDrgBMN2oFA2/BXxX6DeCqcVhQCdQXcuoCvPpgz/l214j3XL2gIG8vF37LpfQ/Ns4CnmNcFeqIOkHl5aLumqm7lkKiebreJq6vdE74zXcOfPJzv8/xS1N901N7vBMBi8p7HAFd2FER6Tx+1m9y56u1vLYWlN3CvIFcuiaSDNxuk9h3phD66VGz0KAb6gIXuru02bnjAAAMrklEQVR1A6q2xVxPeOZDNy9+V+JnJ3IlA4ZeUbXDwk5NVYKK+kRVCHeiC7917M+xElANdYUnSDteMSAN+23CFTRJx7rO99lRpvTOt94HKZtkII4Z9sBZUvSu2yQjqitgOth/dSEBSLtQ79hEtcw1T9Yt82ZBrkOD2i62A2DXckdAKJzvlXC1iLi+Q0qVwYiukCPQdwT5dmHCKpTby6Qjk0JYuDOzkAA0DTIMVUsJoJZRGbJWu2jVmBpWraFqtbNrUg0JWYW1zMrknC1/hjTfa60LwzxX1D6xzxHD2idSmvvRsDJKe9paV0gJIYX5HY75kNY5aNTOP1VB4qgkET0R1Uput57LEMz9aq0nVWWKvV8dhQBrmXP+jZC1fQ/DAHSY6YqjcFF7GbWhXlumjp235ttupSrqMHSjti/rtsEz4l2nblq6Z/t8pvM4IKxBxDRo4Yg7sLSPX6R2XOxjoQplqvdDg94QvrvUvX215E6qU8tvuUohvLvBc40DnvTMMV1fTm60vEHhv0lQ0DRcELXf7dSoeO2ua3OvJT0FWW+5VroK7c3fW7eZPgn6BTFF3T6sX9fM06QB93lvDQ1H3u6sFDOqzvzafc3U8vBaOimrBlD27i2frM+5XT7zL0Plz64Z9rj0TNdWkH7zGx8217UFDRDdYSCsQVMtXxqkHSypSmp366a08zFNgwgD0r6O7eWatRm6mV4Z1WotCHS0eKkKS93e72baKKvmMXO27KFqwDCcxw+QlapZzAhp0KIaEArX8tuQgBYOQWiACIegaVBpvxYW0Kzt1VRwWMuT7fRKC4esdaz81/f8vebgXuJqJ1GD7XDOrUs3RBu2v5PC794dY20N3IQQvwXgQwD/RUr5z9v5Xe3wne//CBtfnbT/i3xLF+3/2kB6qxzslrD3wW36Te100TnD/VivrsXMZ52r7Dfua6L2uUz+yGvx9riuOKmd50TDPEX4bn9dJY1fDUcrFYn2VLPf5vcea7R3oBuf/713669W2ha4CSH+KoCQlPITIcRvCyHuSylftOv72mEmXoY+bkbj3pYabwWVSfj2TKzVWAjHEv913Z/WwswWLsRrqRxp+j2tpgbNN6SVT2m2jvu6t5tf/Gs1heOTvK2XjWpIm21Ls0YJ6fgUby299HxD89pa91K/Wi9nq5730y5IR9vOf3/ZLaHOpT7XhrObbMNfeFFDr88V63N+uNtmPZ/TwX3nPsesrXQkKfX7wqqGbbBOfYtSTcPfK/1WavBezxtavZaafsEldr73XHDuwEatHfUfL2v7wFGr3dJvsdaXrplNzl213f5fVPd7LuJ3XK9w8vq9peGvsM414b9ya3Us3rJVXZ7nd4U2KOP5Zb0+77pUC4L9oa28RX2/56po4V4hb97g/Dg/zY/Txd92mfep/eXcv75b7Pm8C66fVrbX95Ju+kH+2yXtFRukn97vqDuFmrzPlb95vvyiY+9NMVsqF10ibbhK+uzqHeQ65vBv8G3YgGv9Js8+cC6va+ATfmv5b3FtO1v9XUA6Vm2yRjC1s8XtUwDft8b/AMA3AbxTgdvY0TbS+xtXeGeQm5Gv2qZOwXb5qrSGZZmW3nmbcN8RvT1eR2S7bedCcLeM3o7s7gPwM53ejEtpZ+AWB7BljR8B+Jp3BSHELwH4JQCYnJxs46Zcza/+ws+hUK5F466a/EY1tq7aRdFgPhpMXNIV0hK/For6dS5ugvav3Xe/x29/qVYNn/3ku4+Eex3neo123VV+4wWT6nP8arV8t6Nha4RfLZH/ur73mfjUbjnv0fG+11Xr5X3ATRO+v7NBC18r7zXXFU3Xa2U/XvQZtmb7TvqsZ6/j/8yf+v3aKTeWBl1wPTS9B+rC93Z4Jzpcx6ZcuiWsiYs+56r3llxXAbLZ7mp0XNtxuK/UcnjBkzAbXTd+31f39U3e2/r2XeltLecTznX98grnut4076ZuabroGJnreKZbyFNbaul1TtelYfUncSvPM5NSXuq8q61zhbzS+92+29No3Yt/X6PPrH9fC63Jb5EmvE3ZxO/9kZu6X/0atTNwywHotsYT8PnPOCnl9wB8DwC+/vWvByc3t2QSUWQ6vRFERERERPTea2eo+SOY3SMB4DGAV238LiIiIiIiolurnS1u/wnAnwghRgH8LIBvtPG7iIiIiIiIbq22tbhJKbMwH1DypwD+gpTytF3fRUREREREdJu19X/cpJTHqD1ZkoiIiIiIiK7g3XucChERERER0XuGgRsREREREVHAMXAjIiIiIiIKOAZuREREREREAcfAjYiIiIiIKOAYuBEREREREQUcAzciIiIiIqKAY+BGREREREQUcAzciIiIiIiIAo6BGxERERERUcAxcCMiIiIiIgo4Bm5EREREREQBx8CNiIiIiIgo4Bi4ERERERERBRwDNyIiIiIiooBj4EZERERERBRwDNyIiIiIiIgCjoEbERERERFRwDFwIyIiIiIiCjgGbkRERERERAHHwI2IiIiIiCjgGLgREREREREFHAM3IiIiIiKigGPgRkREREREFHAM3IiIiIiIiAKOgRsREREREVHAMXAjIiIiIiIKOAZuREREREREAcfAjYiIiIiIKOAYuBEREREREQUcAzciIiIiIqKAY+BGREREREQUcAzciIiIiIiIAo6BGxERERERUcAxcCMiIiIiIgo4Bm5EREREREQBx8CNiIiIiIgo4Bi4ERERERERBRwDNyIiIiIiooBj4EZERERERBRwDNyIiIiIiIgCjoEbERERERFRwDFwIyIiIiIiCjghpez0NgAAhBD7ANY7vR0+BgAcdHojKBB4LpATzwey8VwgG88FsvFcINtlz4UpKeWg34LABG5BJYT4oZTy653eDuo8ngvkxPOBbDwXyMZzgWw8F8h2necCu0oSEREREREFHAM3IiIiIiKigGPgdrHvdXoDKDB4LpATzwey8VwgG88FsvFcINu1nQu8x42IiIiIiCjg2OJGREREREQUcAzciIiIWiCEGBZC/Ilj+qEQ4j87pr8phFgVQvyREOJ/dGYriegmOdMFIcSkdf3/oRDie8I0JoTYtOb/kRDC9zHvdDsJIUaEEH9JCJG8js9j4ObgufgiQojfF0L8HyHELzaaR7dTC+cCE+L3RAuF9ZQQ4o+t8+NnO7OV1G5CiDSA3wEQt6ZnAfwGgD7Han8WwK9IKT+VUv7Fm99KuiktFNZZXngPeNMFAH8bwC9LKb8NYALAPIA/B+BfWOnCp1LK/c5sLd0ET9rwAYD/COCnAPwvIUTX26YNDNwsPhffrwD4kZTypwD8nBUp+82jW6bFc4EJ8XugxcL6PwXw2wC+BeAfCCHETW8n3YgqgJ8HkLWmzwD8Nc863wDwj4UQT4UQf+cmN45uTouFdZYX3g+udEFK+Y+klP/PWpaB+afL3wDwt4QQPxZC/MvObCbdBJ+04RGAX5BS/jqArwDM4C3TBgZuNd5M+VMA37fG/xjA1xvMo9unlXOBCfH7oZXC+rcA/J6UsgpgBcD0jW0d3RgpZVZKeeqY3pNSljyr/TuY58MnAH5ZCJG5yW2kG9NKYf1TsLxw63nTBZsQ4ucBPJdSbgP4bzDPhz8D4BMhxKOb3Uq6Qd604fcArAsh/gqANIBVvGXawMDN4nPxxQFsWeNHAIYbzKNbpsVzgQnxe6DFwroupcxZ40wX3m9/KKXUpZTnYBB/a7VYWGd54T0lhLgL4FcB/F1r1v+VUp5ZlXtPAdzv2MZRWzVIGxIA/jqAdQASb5k2MHBrLAeg2xpPwNxXfvPo9vM77kyIyVZ1jDNdeE9ZXWT/txAiIYQYBvAEZu0qvQd8CussL7yHrK5y/wHALzoK8J9ZD6joAfCXAXzRsQ2kGyelPJFS/k0AEZiV/W+VNjAhaexHAL5pjT8G8KrBPLr9/I47E2KyPRdC2F0dHsOsVaP3jDT/FPVfw6zI+e8A/r5fqwzdPg0K6ywvvJ/+IYBJAP/GemDNnwfw6wD+J4A/BfBvpZQrndxAujlCiN8UQnzLmkwBOMFbpg3ha9u62+d3APxXIcRPA/gQwA9gNm1659Ht53cu2AlxGUyI33e/CeC3hBA/AHAmpdy66A307pJSftpoWkr5uwB+94Y3iTrPWVgHgH8C/3yDbik7HZBS/hqAX/NZZe5GN4iC4l8B+PdCCAngD6SUK0KIt0obhFlJSH6EEKMwo+LP7Fo0v3l0+/G4UzNCiHsAFgD8vs89cET0HmK+QUR+3iZtYOBGREREREQUcLzHjYiIiIiIKOAYuBEREREREQUcAzciIiIiIqKAY+BGREREREQUcAzciIiIiIiIAu7/A/jYqL/iGO/2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 20))\n",
    "for i in range(11,len(data.columns)):\n",
    "    plt.plot(data.iloc[100:130][data.columns[i]], label=data.columns[i])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "index 80 is out of bounds for axis 0 with size 29",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-129-299cd91de15e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m15\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m8\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m11\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m     \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mD:\\soft\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexes\\base.py\u001b[0m in \u001b[0;36m__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m   3956\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mis_scalar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3957\u001b[0m             \u001b[0mkey\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcast_scalar_indexer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 3958\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mgetitem\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   3959\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3960\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mslice\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mIndexError\u001b[0m: index 80 is out of bounds for axis 0 with size 29"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "for c in range(11, len(data.columns)):\n",
    "    plt.plot(data[data.columns[i]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_133 = data_325[ data_325['样本编号']==133 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_range = pd.read_excel(\"主要变量的操作范围.xlsx\", na_values=np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = list(feature_range[\"name\"].T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['S-ZORB.CAL_H2.PV',\n",
       " 'S-ZORB.FC_2801.PV',\n",
       " 'S-ZORB.FT_5101.PV',\n",
       " 'S-ZORB.FT_9001.PV',\n",
       " 'S-ZORB.LC_5001.PV',\n",
       " 'S-ZORB.LC_5101.PV',\n",
       " 'S-ZORB.PC_2105.PV',\n",
       " 'S-ZORB.PC_5101.PV',\n",
       " 'S-ZORB.PDT_2104.PV',\n",
       " 'S-ZORB.PT_2101.PV',\n",
       " 'S-ZORB.PT_2801.PV',\n",
       " 'S-ZORB.TC_5005.PV',\n",
       " 'S-ZORB.TE_2005.PV',\n",
       " 'S-ZORB.TE_2103.PV',\n",
       " 'S-ZORB.TE_2301.PV',\n",
       " 'S-ZORB.TE_5102.PV',\n",
       " 'S-ZORB.TE_5202.PV',\n",
       " 'S-ZORB.TE_9001.PV']"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['样本编号', '时间', 'RON损失', '原料性质：硫含量', '原料性质：辛烷值', '原料性质：饱和烃', '原料性质：烯烃',\n",
       "       '原料性质：芳烃', '原料性质：溴值', '原料性质：密度', '产品性质：硫含量', '产品性质：辛烷值', '待生吸附剂性质：焦炭',\n",
       "       '待生吸附剂性质：S', '再生吸附剂性质：焦炭', '再生吸附剂性质：S', 'S-ZORB.CAL_H2.PV',\n",
       "       'S-ZORB.PDI_2102.PV', 'S-ZORB.PT_2801.PV', 'S-ZORB.FC_2801.PV',\n",
       "       'S-ZORB.TE_2103.PV', 'S-ZORB.TE_2005.PV', 'S-ZORB.PT_2101.PV',\n",
       "       'S-ZORB.PDT_2104.PV', 'S-ZORB.TE_2301.PV', 'S-ZORB.PT_2301.PV',\n",
       "       'S-ZORB.PC_2105.PV', 'S-ZORB.PC_5101.PV', 'S-ZORB.TC_5005.PV',\n",
       "       'S-ZORB.LC_5001.PV'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_133.columns[:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_names = ['RON损失', '原料性质：硫含量', '原料性质：辛烷值', '原料性质：饱和烃', '原料性质：烯烃',\n",
    "       '原料性质：溴值', '原料性质：密度',  '待生吸附剂性质：焦炭',\n",
    "       '待生吸附剂性质：S', '再生吸附剂性质：焦炭', '再生吸附剂性质：S','S-ZORB.CAL_H2.PV',\n",
    " 'S-ZORB.FC_2801.PV',\n",
    " 'S-ZORB.FT_5101.PV',\n",
    " 'S-ZORB.FT_9001.PV',\n",
    " 'S-ZORB.LC_5001.PV',\n",
    " 'S-ZORB.LC_5101.PV',\n",
    " 'S-ZORB.PC_2105.PV',\n",
    " 'S-ZORB.PC_5101.PV',\n",
    " 'S-ZORB.PDT_2104.PV',\n",
    " 'S-ZORB.PT_2101.PV',\n",
    " 'S-ZORB.PT_2801.PV',\n",
    " 'S-ZORB.TC_5005.PV',\n",
    " 'S-ZORB.TE_2005.PV',\n",
    " 'S-ZORB.TE_2103.PV',\n",
    " 'S-ZORB.TE_2301.PV',\n",
    " 'S-ZORB.TE_5102.PV',\n",
    " 'S-ZORB.TE_5202.PV',\n",
    " 'S-ZORB.TE_9001.PV']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(feature_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_133 = data_133[feature_names]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RON损失</th>\n",
       "      <th>原料性质：硫含量</th>\n",
       "      <th>原料性质：辛烷值</th>\n",
       "      <th>原料性质：饱和烃</th>\n",
       "      <th>原料性质：烯烃</th>\n",
       "      <th>原料性质：溴值</th>\n",
       "      <th>原料性质：密度</th>\n",
       "      <th>待生吸附剂性质：焦炭</th>\n",
       "      <th>待生吸附剂性质：S</th>\n",
       "      <th>再生吸附剂性质：焦炭</th>\n",
       "      <th>...</th>\n",
       "      <th>S-ZORB.PDT_2104.PV</th>\n",
       "      <th>S-ZORB.PT_2101.PV</th>\n",
       "      <th>S-ZORB.PT_2801.PV</th>\n",
       "      <th>S-ZORB.TC_5005.PV</th>\n",
       "      <th>S-ZORB.TE_2005.PV</th>\n",
       "      <th>S-ZORB.TE_2103.PV</th>\n",
       "      <th>S-ZORB.TE_2301.PV</th>\n",
       "      <th>S-ZORB.TE_5102.PV</th>\n",
       "      <th>S-ZORB.TE_5202.PV</th>\n",
       "      <th>S-ZORB.TE_9001.PV</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>1.31</td>\n",
       "      <td>248.0</td>\n",
       "      <td>89.4</td>\n",
       "      <td>55.9</td>\n",
       "      <td>20.6</td>\n",
       "      <td>50.11</td>\n",
       "      <td>727.8</td>\n",
       "      <td>2.53</td>\n",
       "      <td>8.57</td>\n",
       "      <td>1.3</td>\n",
       "      <td>...</td>\n",
       "      <td>82.388954</td>\n",
       "      <td>2.361462</td>\n",
       "      <td>2.476889</td>\n",
       "      <td>124.658965</td>\n",
       "      <td>420.101342</td>\n",
       "      <td>426.61955</td>\n",
       "      <td>380.73177</td>\n",
       "      <td>25.778817</td>\n",
       "      <td>34.452484</td>\n",
       "      <td>13.618144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     RON损失  原料性质：硫含量  原料性质：辛烷值  原料性质：饱和烃  原料性质：烯烃  原料性质：溴值  原料性质：密度  \\\n",
       "102   1.31     248.0      89.4      55.9     20.6    50.11    727.8   \n",
       "\n",
       "     待生吸附剂性质：焦炭  待生吸附剂性质：S  再生吸附剂性质：焦炭  ...  S-ZORB.PDT_2104.PV  \\\n",
       "102        2.53       8.57         1.3  ...           82.388954   \n",
       "\n",
       "     S-ZORB.PT_2101.PV  S-ZORB.PT_2801.PV  S-ZORB.TC_5005.PV  \\\n",
       "102           2.361462           2.476889         124.658965   \n",
       "\n",
       "     S-ZORB.TE_2005.PV  S-ZORB.TE_2103.PV  S-ZORB.TE_2301.PV  \\\n",
       "102         420.101342          426.61955          380.73177   \n",
       "\n",
       "     S-ZORB.TE_5102.PV  S-ZORB.TE_5202.PV  S-ZORB.TE_9001.PV  \n",
       "102          25.778817          34.452484          13.618144  \n",
       "\n",
       "[1 rows x 29 columns]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_133.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = data_133[feature_names[1:]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = data_133['RON损失']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_range = pd.read_excel(\"主要变量的操作范围.xlsx\",index_col=0 , na_values=np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>step</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>S-ZORB.CAL_H2.PV</th>\n",
       "      <td>0.20</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.01</td>\n",
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       "    <tr>\n",
       "      <th>S-ZORB.FC_2801.PV</th>\n",
       "      <td>600.00</td>\n",
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       "      <th>S-ZORB.FT_5101.PV</th>\n",
       "      <td>430.00</td>\n",
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       "    <tr>\n",
       "      <th>S-ZORB.FT_9001.PV</th>\n",
       "      <td>350.00</td>\n",
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       "      <td>50.00</td>\n",
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       "    <tr>\n",
       "      <th>S-ZORB.LC_5001.PV</th>\n",
       "      <td>45.00</td>\n",
       "      <td>60.00</td>\n",
       "      <td>1.00</td>\n",
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       "    <tr>\n",
       "      <th>S-ZORB.LC_5101.PV</th>\n",
       "      <td>40.00</td>\n",
       "      <td>800.00</td>\n",
       "      <td>50.00</td>\n",
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       "    <tr>\n",
       "      <th>S-ZORB.PC_2105.PV</th>\n",
       "      <td>4.50</td>\n",
       "      <td>5.85</td>\n",
       "      <td>0.10</td>\n",
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       "    <tr>\n",
       "      <th>S-ZORB.PC_5101.PV</th>\n",
       "      <td>0.60</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.PDT_2104.PV</th>\n",
       "      <td>50.00</td>\n",
       "      <td>110.00</td>\n",
       "      <td>5.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.PT_2101.PV</th>\n",
       "      <td>2.25</td>\n",
       "      <td>2.55</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.PT_2801.PV</th>\n",
       "      <td>2.35</td>\n",
       "      <td>2.70</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TC_5005.PV</th>\n",
       "      <td>100.00</td>\n",
       "      <td>150.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TE_2005.PV</th>\n",
       "      <td>399.00</td>\n",
       "      <td>430.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TE_2103.PV</th>\n",
       "      <td>410.00</td>\n",
       "      <td>435.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TE_2301.PV</th>\n",
       "      <td>240.00</td>\n",
       "      <td>400.00</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TE_5102.PV</th>\n",
       "      <td>20.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TE_5202.PV</th>\n",
       "      <td>30.00</td>\n",
       "      <td>45.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>S-ZORB.TE_9001.PV</th>\n",
       "      <td>10.00</td>\n",
       "      <td>40.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       min      max   step\n",
       "name                                      \n",
       "S-ZORB.CAL_H2.PV      0.20     0.37   0.01\n",
       "S-ZORB.FC_2801.PV   600.00  1000.00  50.00\n",
       "S-ZORB.FT_5101.PV   430.00  1500.00  50.00\n",
       "S-ZORB.FT_9001.PV   350.00   600.00  50.00\n",
       "S-ZORB.LC_5001.PV    45.00    60.00   1.00\n",
       "S-ZORB.LC_5101.PV    40.00   800.00  50.00\n",
       "S-ZORB.PC_2105.PV     4.50     5.85   0.10\n",
       "S-ZORB.PC_5101.PV     0.60     0.70   0.05\n",
       "S-ZORB.PDT_2104.PV   50.00   110.00   5.00\n",
       "S-ZORB.PT_2101.PV     2.25     2.55   0.10\n",
       "S-ZORB.PT_2801.PV     2.35     2.70   0.10\n",
       "S-ZORB.TC_5005.PV   100.00   150.00   1.00\n",
       "S-ZORB.TE_2005.PV   399.00   430.00   1.00\n",
       "S-ZORB.TE_2103.PV   410.00   435.00   1.00\n",
       "S-ZORB.TE_2301.PV   240.00   400.00   2.00\n",
       "S-ZORB.TE_5102.PV    20.00    40.00   1.00\n",
       "S-ZORB.TE_5202.PV    30.00    45.00   1.00\n",
       "S-ZORB.TE_9001.PV    10.00    40.00   1.00"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_RFR = RandomForestRegressor(max_depth=5, n_estimators=100, random_state=666)\n",
    "model_RFR.fit(X, y)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "y_predict = model_RFR.predict(x_text)\n",
    "mse_score = MSE(y, y_predict)\n",
    "rmse_score = np.sqrt(mse_score)\n",
    "mae_score = mean_absolute_error(y_test_ron_loss, y_ron_loss_predict_1)\n",
    "rr_score = r2_score(y_test_ron_loss, y_ron_loss_predict_1)\n",
    "print(\"随机森林回归模型\")\n",
    "print(\"MSE_SCORE = \", mse_score)\n",
    "print(\"RMSE_SCORE = \", rmse_score)\n",
    "print(\"R_Square = \", rr_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# X = data[ feature_names_list[:28] ]\n",
    "# y_ron_loss = data[ feature_names_list[29] ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# x_train_ron_loss, x_test_ron_loss, y_train_ron_loss, y_test_ron_loss = train_test_split(X, y_ron_loss, test_size=0.3, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "#x_train_ron_loss.columns[:29]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "#x_train, x_test, y_train, y_test = x_train_ron_loss.iloc[:-2],x_test_ron_loss.iloc[:-2],y_train_ron_loss.iloc[-1],y_test_ron_loss.iloc[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#x_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.svm import SVR\n",
    "from sklearn.linear_model import Lasso\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.tree import ExtraTreeRegressor\n",
    "from xgboost import XGBRegressor\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.ensemble import AdaBoostRegressor\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from sklearn.ensemble import BaggingRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "随机森林回归模型\n",
      "MSE_SCORE =  0.03950825733051347\n",
      "RMSE_SCORE =  0.1987668416273536\n",
      "R_Square =  0.07098332106835259\n"
     ]
    }
   ],
   "source": [
    "model_RFR = RandomForestRegressor(max_depth=5, n_estimators=100, random_state=666)\n",
    "model_RFR.fit(x_train_ron_loss, y_train_ron_loss)\n",
    "y_ron_loss_predict_1 = model_RFR.predict(x_test_ron_loss)\n",
    "model_fearture = model_RFR.feature_importances_\n",
    "mse_score = MSE(y_test_ron_loss, y_ron_loss_predict_1)\n",
    "rmse_score = np.sqrt(mse_score)\n",
    "mae_score = mean_absolute_error(y_test_ron_loss, y_ron_loss_predict_1)\n",
    "rr_score = r2_score(y_test_ron_loss, y_ron_loss_predict_1)\n",
    "print(\"随机森林回归模型\")\n",
    "print(\"MSE_SCORE = \", mse_score)\n",
    "print(\"RMSE_SCORE = \", rmse_score)\n",
    "print(\"R_Square = \", rr_score)\n",
    "\n",
    "# model_RFR = RandomForestRegressor(max_depth=5, n_estimators=100, random_state=666)\n",
    "# model_RFR.fit(x_train, y_train)\n",
    "# y_predict = model_RFR.predict(x_test)\n",
    "# model_fearture = model_RFR.feature_importances_\n",
    "# mse_score = MSE(y_test, y_predict)\n",
    "# rmse_score = np.sqrt(mse_score)\n",
    "# mae_score = mean_absolute_error(y_test, y_predict)\n",
    "# rr_score = r2_score(y_test, y_predict)\n",
    "# print(\"随机森林回归模型\")\n",
    "# print(\"MSE_SCORE = \", mse_score)\n",
    "# print(\"RMSE_SCORE = \", rmse_score)\n",
    "# print(\"R_Square = \", rr_score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "res = x_test_ron_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = res.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "res.to_excel(\"res.xlsx\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.31635162, 1.22099086, 1.34769623, 1.16193617, 1.28266473,\n",
       "       1.41687763, 1.44724321, 1.30363243, 1.25912475, 1.16021289,\n",
       "       1.26789484, 1.06729279, 1.19117836, 1.27779582, 1.13770678,\n",
       "       1.20026467, 1.30041962, 1.29483589, 1.21256905, 1.24085787,\n",
       "       1.32255873, 1.38747749, 1.16968421, 1.4545376 , 1.19340734,\n",
       "       1.17804959, 1.19972475, 1.21145862, 1.36908996, 1.25328887,\n",
       "       1.25017148, 1.29019223, 1.19437836, 1.3664641 , 1.33043592,\n",
       "       1.27997628, 1.3404612 , 1.37517264, 1.3719264 , 1.26768898,\n",
       "       1.30144652, 1.29469462, 1.32523104, 1.3219021 , 1.17483386,\n",
       "       1.28358891, 1.2215375 , 1.17856932, 1.22868352, 1.19192682,\n",
       "       1.43002311, 1.17556407, 1.46711323, 1.34186061, 1.36918835,\n",
       "       1.23417965, 1.27922015, 1.20600361, 1.22273385, 1.31916455,\n",
       "       1.29498246, 1.2276392 , 1.31846878, 1.2023313 , 1.28334481,\n",
       "       1.34291945, 1.40991347, 1.26962263, 1.30751329, 1.22190678,\n",
       "       1.20043576, 1.29133705, 1.21164295, 1.25329847, 1.24387232,\n",
       "       1.18859453, 1.17347765, 1.23598077, 1.36230378, 1.15419847,\n",
       "       1.32091508])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# y_ron_loss_predict_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.7 , 1.4 , 1.1 , 1.34, 1.2 , 1.2 , 1.3 , 1.21, 1.4 , 1.34, 1.1 ,\n",
       "       1.04, 1.22, 1.38, 1.21, 1.34, 1.81, 1.18, 1.28, 1.05, 1.28, 1.51,\n",
       "       1.3 , 1.38, 1.15, 1.2 , 1.25, 1.22, 1.5 , 1.7 , 1.25, 1.44, 1.2 ,\n",
       "       1.3 , 1.41, 1.28, 1.8 , 1.75, 1.42, 1.1 , 1.68, 1.22, 1.6 , 1.08,\n",
       "       1.12, 1.28, 1.44, 1.3 , 1.05, 1.41, 0.81, 1.11, 1.51, 1.31, 1.61,\n",
       "       1.3 , 1.18, 1.2 , 1.14, 1.41, 1.4 , 1.22, 1.24, 1.22, 1.4 , 1.54,\n",
       "       1.68, 0.91, 1.38, 1.31, 1.25, 1.78, 1.21, 1.11, 1.51, 1.51, 1.02,\n",
       "       1.28, 1.58, 1.01, 1.2 ])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# y = np.array(y_test_ron_loss)\n",
    "# y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.22567551543375336\n",
      "0.1278636696640641\n",
      "-0.22517838794719902\n",
      "0.13288345797694076\n",
      "-0.06888727817328819\n",
      "-0.18073135723480507\n",
      "-0.1132640058549135\n",
      "-0.0773821724107079\n",
      "0.10062517544869394\n",
      "0.13416948399925024\n",
      "-0.15263167206083694\n",
      "-0.026243070752491472\n",
      "0.023624296552723974\n",
      "0.07406100352107033\n",
      "0.05974646322960121\n",
      "0.1042800935164922\n",
      "0.2815361217533533\n",
      "-0.09731855430526638\n",
      "0.05268043287240938\n",
      "-0.18176939746716658\n",
      "-0.03324900853352383\n",
      "0.0811407343885901\n",
      "0.10024291654373443\n",
      "-0.054012756460916064\n",
      "-0.037745515294120464\n",
      "0.01829200927743223\n",
      "0.04022020013957679\n",
      "0.007001130561439365\n",
      "0.08727336091708156\n",
      "0.26277125455542394\n",
      "-0.00013718779367497547\n",
      "0.1040331747193803\n",
      "0.004684698862748385\n",
      "-0.051126231506907066\n",
      "0.056428423222912166\n",
      "1.8529624083545013e-05\n",
      "0.2552993351419516\n",
      "0.21418706508142954\n",
      "0.03385465102510388\n",
      "-0.15244452394504132\n",
      "0.22532944942041508\n",
      "-0.06122510081176272\n",
      "0.17173059810073313\n",
      "-0.22398342773197805\n",
      "-0.048958807178984085\n",
      "-0.002803838374587813\n",
      "0.15171007122598332\n",
      "0.09340821701506304\n",
      "-0.17017477888863447\n",
      "0.15466183049834448\n",
      "-0.7654606349280287\n",
      "-0.05906673354578714\n",
      "0.028401832143488844\n",
      "-0.024321075436505357\n",
      "0.14957245204571856\n",
      "0.05063103692746762\n",
      "-0.08408486890211844\n",
      "-0.005003007014901886\n",
      "-0.07257355178224764\n",
      "0.06442230630340791\n",
      "0.07501252907997238\n",
      "-0.006261637621526558\n",
      "-0.06328127429505302\n",
      "0.014482539048608505\n",
      "0.08332513787477645\n",
      "0.1279743814449824\n",
      "0.1607657932059997\n",
      "-0.39518970304364354\n",
      "0.05252659947509448\n",
      "0.06724673616873048\n",
      "0.03965139001051554\n",
      "0.2745297444118999\n",
      "-0.0013578108220654126\n",
      "-0.12909772190314933\n",
      "0.1762434994707925\n",
      "0.2128513056572642\n",
      "-0.15046828448074567\n",
      "0.034390027225410555\n",
      "0.1377824176081626\n",
      "-0.142770758192187\n",
      "-0.10076256632816982\n"
     ]
    }
   ],
   "source": [
    "# for i in range(len(y)):\n",
    "#     loss = (y[i] - y_ron_loss_predict_1[i])/y[i]\n",
    "#     print(loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "language_info": {
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    "name": "ipython",
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   "file_extension": ".py",
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